Patent Publication Number: US-2018048907-A1

Title: Video coding tools for in-loop sample processing

Description:
This application claims the benefit of U.S. Provisional Application No. 62/373,884, filed on 11 Aug. 2016, the entire contents of which are hereby incorporated by reference. 
    
    
     TECHNICAL FIELD 
     This disclosure relates to video encoding and video decoding. 
     BACKGROUND 
     Digital video capabilities can be incorporated into a wide range of device s, including digital televisions, digital direct broadcast systems, wireless broadcast systems, personal digital assistants (PDAs), laptop or desktop computers, tablet computers, e-book readers, digital cameras, digital recording devices, digital media players, video gaming devices, video game consoles, cellular or satellite radio telephones, so-called “smart phones,” video teleconferencing devices, video streaming devices, and the like. Digital video devices implement video coding techniques, such as those described in the standards defined by ITU-T H.261, ISO/IEC MPEG-1 ITU-T H.262 or ISO/IEC MPEG-2 Visual, MPEG-2, MPEG-4, MPEG-4 Visual, ITU-T H.263, ITU-T H.264/MPEG-4, Part 10, Advanced Video Coding (AVC), ISO/IEC MPEG-4 AVC ITU-T H.265, High Efficiency Video Coding (HEVC), and extensions of any of these standards, such as the Scalable Video Coding (SVC) and/or Multi-View Video Coding (MVC) extensions. The video devices may transmit, receive, encode, decode, and/or store digital video information more efficiently by implementing such video coding techniques. 
     Video coding techniques include spatial (intra-picture) prediction and/or temporal (inter-picture) prediction to reduce or remove redundancy inherent in video sequences. For block-based video coding, a video slice (e.g., a video frame or a portion of a video frame) may be partitioned into video blocks, which may also be referred to as treeblocks, coding units (CUs) and/or coding nodes. Video blocks in an intra-coded (I) slice of a picture are encoded using spatial prediction with respect to reference samples in neighboring blocks in the same picture. Video blocks in an inter-coded (P or B) slice of a picture may use spatial prediction with respect to reference samples in neighboring blocks in the same picture or temporal prediction with respect to reference samples in other reference pictures. Pictures may be referred to as frames, and reference pictures may be referred to as reference frames. 
     Spatial or temporal prediction results in a predictive block for a block to be coded. Residual data represents pixel differences between the original block to be coded and the predictive block. An inter-coded block is encoded according to a motion vector that points to a block of reference samples forming the predictive block, and the residual data indicating the difference between the coded block and the predictive block. An intra-coded block is encoded according to an intra-coding mode and the residual data. For further compression, the residual data may be transformed from the pixel domain to a transform domain, resulting in residual transform coefficients, which then may be quantized. The quantized transform coefficients, initially arranged in a two-dimensional array, may be scanned in order to produce a one-dimensional vector of transform coefficients, and entropy coding may be applied to achieve even more compression. 
     SUMMARY 
     In general, this disclosure describes techniques related to coding (e.g., decoding or encoding) of video data. In some examples, the techniques of this disclosure are directed to the coding of video signals with High Dynamic Range (HDR) and Wide Color Gamut (WCG) representations. The described techniques may be used in the context of advanced video codecs, such as extensions of HEVC or the next generation of video coding standards. 
     In one example, a device for coding video data includes a memory and processing circuitry in communication with the memory. The memory is configured to store video data including a current block. The processing circuitry is configured to obtain a parameter value that is based on one or more corresponding parameter values associated with one or more neighbor blocks of the video data stored to the memory. The one or more neighbor blocks are positioned within a spatio-temporal neighborhood of the current block. The spatio-temporal neighborhood includes one or more spatial neighbor blocks that are positioned adjacent to the current block and a temporal neighbor block that is pointed to by a disparity vector (DV) associated with the current block. The obtained parameter value is used to modify residual data associated with the current block in a coding process. The processing circuitry is further configured to code the current block of the video data stored to the memory. 
     In another example, a method of coding a current block of video data includes obtaining a parameter value that is based on one or more corresponding parameter values associated with one or more neighbor blocks of the video data positioned within a spatio-temporal neighborhood of the current block. The spatio-temporal neighborhood includes one or more spatial neighbor blocks that are positioned adjacent to the current block and a temporal neighbor block that is pointed to by a disparity vector (DV) associated with the current block. The obtained parameter value is used to modify residual data associated with the current block in a coding process. The method further includes coding the current block of the video data based on the obtained parameter value. 
     In another example, an apparatus for coding video includes means for obtaining a parameter value that is based on one or more corresponding parameter values associated with one or more neighbor blocks of the video data positioned within a spatio-temporal neighborhood of a current block of the video data, where the spatio-temporal neighborhood includes one or more spatial neighbor blocks that are positioned adjacent to the current block and a temporal neighbor block that is pointed to by a disparity vector (DV) associated with the current block, and where the obtained parameter value is used to modify residual data associated with the current block in a coding process. The apparatus further includes means for coding the current block of the video data based on the obtained parameter value. 
     In another example, a non-transitory computer-readable storage medium is encoded with instructions that, when executed, cause processing circuitry of a video coding device to obtain a parameter value that is based on one or more corresponding parameter values associated with one or more neighbor blocks of the video data positioned within a spatio-temporal neighborhood of a current block of the video data, the spatio-temporal neighborhood including one or more spatial neighbor blocks that are positioned adjacent to the current block and a temporal neighbor block that is pointed to by a disparity vector (DV) associated with the current block, where the obtained parameter value is used to modify residual data associated with the current block in a coding process, and to code the current block of the video data based on the obtained parameter value. 
     The details of one or more examples are set forth in the accompanying drawings and the description below. Other features, objects, and advantages will be apparent from the description and drawings, and from the claims. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is a block diagram illustrating an example video encoding and decoding system configured to implement techniques of the disclosure. 
         FIG. 2  is a conceptual drawing illustrating the concepts of high dynamic range data. 
         FIG. 3  is a conceptual diagram illustrating example color gamuts. 
         FIG. 4  is a flow diagram illustrating an example of High Dynamic Range (HDR)/Wide Color Gamut (WCG) representation conversion. 
         FIG. 5  is a flow diagram showing an example HDR/WCG inverse conversion. 
         FIG. 6  is conceptual diagram illustrating example transfer functions. 
         FIG. 7  is a block diagram illustrating an example for non-constant luminance. 
         FIG. 8  is a block diagram illustrating techniques of this disclosure for derivation of quantization parameters or scaling parameters from the spatio-temporal neighborhood of a block being coded currently. 
         FIG. 9  is a block diagram illustrating an example of a video encoder. 
         FIG. 10  is a block diagram illustrating an example of a video decoder. 
         FIG. 11  is a flowchart illustrating an example process by which a video decoder may implement techniques of this disclosure. 
         FIG. 12  is a flowchart illustrating an example process by which a video decoder may implement techniques of this disclosure. 
         FIG. 13  is a flowchart illustrating an example process by which a video encoder may implement techniques of this disclosure. 
         FIG. 14  is a flowchart illustrating an example process by which a video encoder may implement techniques of this disclosure. 
     
    
    
     DETAILED DESCRIPTION 
     This disclosure is related to coding of video signals with High Dynamic Range (HDR) and Wide Color Gamut (WCG) representations. More specifically, the techniques of this disclosure include signaling and operations applied to video data in certain color spaces to enable more efficient compression of HDR and WCG video data. The proposed techniques may improve compression efficiency of hybrid based video coding systems (e.g., HEVC-based video coders) used for coding HDR and WCG video data. The details of one or more examples of the disclosure are set forth in the accompanying drawings and the description below. Other features, objects, and advantages will be apparent from the description, drawings, and claims. 
       FIG. 1  is a block diagram illustrating an example video encoding and decoding system  10  that may utilize techniques of this disclosure. As shown in  FIG. 1 , system  10  includes a source device  12  that provides encoded video data to be decoded at a later time by a destination device  14 . In particular, source device  12  provides the video data to destination device  14  via a computer-readable medium  16 . Source device  12  and destination device  14  may comprise any of a wide range of devices, including desktop computers, notebook (i.e., laptop) computers, tablet computers, set-top boxes, telephone handsets such as so-called “smart” phones, so-called “smart” pads, televisions, cameras, display devices, digital media players, video gaming consoles, video streaming device, or the like. In some cases, source device  12  and destination device  14  may be equipped for wireless communication. 
     In the example of  FIG. 1 , source device  12  includes video source  18 , video encoding unit  21 , which includes video preprocessor unit  19  and video encoder  20 , and output interface  22 . Destination device  14  includes input interface  28 , video decoding unit  29 , which includes video decoder  30  and video postprocessor unit  31 , and display device  32 . In accordance with some example of this disclosure, video preprocessor unit  19  and video postprocessor unit  31  may be configured to perform all or parts of particular techniques described in this disclosure. For example, video preprocessor unit  19  and video postprocessor unit  31  may include a static transfer function unit configured to apply a static transfer function, but with pre- and post-processing units that can adapt signal characteristics. 
     In other examples, a source device and a destination device may include other components or arrangements. For example, source device  12  may receive video data from an external video source  18 , such as an external camera. Likewise, destination device  14  may interface with an external display device, rather than including an integrated display device. 
     The illustrated system  10  of  FIG. 1  is merely one example. Techniques for processing video data may be performed by any digital video encoding and/or decoding device. Although generally the techniques of this disclosure are performed by a video encoding device, the techniques may also be performed by a video encoder/decoder, typically referred to as a “CODEC.” For ease of description, the disclosure is described with respect to video preprocessor unit  19  and video postprocessor unit  31  performing the example techniques described in this disclosure in respective ones of source device  12  and destination device  14 . Source device  12  and destination device  14  are merely examples of such coding devices in which source device  12  generates coded video data for transmission to destination device  14 . In some examples, devices  12 ,  14  may operate in a substantially symmetrical manner such that each of devices  12 ,  14  include video encoding and decoding components. Hence, system  10  may support one-way or two-way video transmission between video devices  12 ,  14 , e.g., for video streaming, video playback, video broadcasting, or video telephony. 
     Video source  18  of source device  12  may include a video capture device, such as a video camera, a video archive containing previously captured video, and/or a video feed interface to receive video data from a video content provider. As a further alternative, video source  18  may generate computer graphics-based data as the source video, or a combination of live video, archived video, and computer-generated video. In some cases, if video source  18  is a video camera, source device  12  and destination device  14  may form so-called camera phones or video phones. Source device  12  may comprise one or more data storage media configured to store the video data. As mentioned above, however, the techniques described in this disclosure may be applicable to video coding in general, and may be applied to wireless and/or wired applications. In each case, the captured, pre-captured, or computer-generated video may be encoded by video encoding unit  21 . The encoded video information may then be output by output interface  22  onto a computer-readable medium  16 . 
     Destination device  14  may receive the encoded video data to be decoded via computer-readable medium  16 . Computer-readable medium  16  may comprise any type of medium or device capable of moving the encoded video data from source device  12  to destination device  14 . In one example, computer-readable medium  16  may comprise a communication medium to enable source device  12  to transmit encoded video data directly to destination device  14  in real-time. The encoded video data may be modulated according to a communication standard, such as a wireless communication protocol, and transmitted to destination device  14 . The communication medium may comprise any wireless or wired communication medium, such as a radio frequency (RF) spectrum or one or more physical transmission lines. The communication medium may form part of a packet-based network, such as a local area network, a wide-area network, or a global network such as the Internet. The communication medium may include routers, switches, base stations, or any other equipment that may be useful to facilitate communication from source device  12  to destination device  14 . Destination device  14  may comprise one or more data storage media configured to store encoded video data and decoded video data. 
     In some examples, encoded data may be output from output interface  22  to a storage device. Similarly, encoded data may be accessed from the storage device by input interface. The storage device may include any of a variety of distributed or locally accessed data storage media such as a hard drive, Blu-ray discs, DVDs, CD-ROMs, flash memory, volatile or non-volatile memory, or any other suitable digital storage media for storing encoded video data. In a further example, the storage device may correspond to a file server or another intermediate storage device that may store the encoded video generated by source device  12 . Destination device  14  may access stored video data from the storage device via streaming or download. The file server may be any type of server capable of storing encoded video data and transmitting that encoded video data to the destination device  14 . Example file servers include a web server (e.g., for a website), an FTP server, network attached storage (NAS) devices, or a local disk drive. Destination device  14  may access the encoded video data through any standard data connection, including an Internet connection. This may include a wireless channel (e.g., a Wi-Fi connection), a wired connection (e.g., DSL, cable modem, etc.), or a combination of both that is suitable for accessing encoded video data stored on a file server. The transmission of encoded video data from the storage device may be a streaming transmission, a download transmission, or a combination thereof. 
     The techniques of this disclosure are not necessarily limited to wireless applications or settings. The techniques may be applied to video coding in support of any of a variety of multimedia applications, such as over-the-air television broadcasts, cable television transmissions, satellite television transmissions, Internet streaming video transmissions, such as dynamic adaptive streaming over HTTP (DASH), digital video that is encoded onto a data storage medium, decoding of digital video stored on a data storage medium, or other applications. In some examples, system  10  may be configured to support one-way or two-way video transmission to support applications such as video streaming, video playback, video broadcasting, and/or video telephony. 
     Computer-readable medium  16  may include transient media, such as a wireless broadcast or wired network transmission, or storage media (that is, non-transitory storage media), such as a hard disk, flash drive, compact disc, digital video disc, Blu-ray disc, or other computer-readable media. In some examples, a network server (not shown) may receive encoded video data from source device  12  and provide the encoded video data to destination device  14 , e.g., via network transmission. Similarly, a computing device of a medium production facility, such as a disc stamping facility, may receive encoded video data from source device  12  and produce a disc containing the encoded video data. Therefore, computer-readable medium  16  may be understood to include one or more computer-readable media of various forms, in various examples. 
     Input interface  28  of destination device  14  receives information from computer-readable medium  16 . The information of computer-readable medium  16  may include syntax information defined by video encoder  20  of video encoding unit  21 , which is also used by video decoder  30  of video decoding unit  29 , that includes syntax elements that describe characteristics and/or processing of blocks and other coded units, e.g., groups of pictures (GOPs). Display device  32  displays the decoded video data to a user, and may comprise any of a variety of display devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), a plasma display, an organic light emitting diode (OLED) display, or another type of display device. 
     As illustrated, video preprocessor unit  19  receives the video data from video source  18 . Video preprocessor unit  19  may be configured to process the video data to convert the video data into a form that is suitable for encoding with video encoder  20 . For example, video preprocessor unit  19  may perform dynamic range compacting (e.g., using a non-linear transfer function), color conversion to a more compact or robust color space, and/or floating-to-integer representation conversion. Video encoder  20  may perform video encoding on the video data outputted by video preprocessor unit  19 . Video decoder  30  may perform the inverse of video encoder  20  to decode video data, and video postprocessor unit  31  may perform the inverse of the operations performed by video preprocessor unit  19  to convert the video data into a form suitable for display. For instance, video postprocessor unit  31  may perform integer-to-floating conversion, color conversion from the compact or robust color space, and/or inverse of the dynamic range compacting to generate video data suitable for display. 
     Video encoding unit  21  and video decoding unit  29  each may be implemented as any of a variety of suitable processing circuitry, including fixed function processing circuitry and/or programmable processing circuitry, such as one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), discrete logic, software, hardware, firmware or any combinations thereof. When the techniques are implemented partially in software, a device may store instructions for the software in a suitable, non-transitory computer-readable medium and execute the instructions in hardware using one or more processors to perform the techniques of this disclosure. Each of video encoding unit  21  and video decoding unit  29  may be included in one or more encoders or decoders, either of which may be integrated as part of a combined encoder/decoder (CODEC) in a respective device. 
     Although video preprocessor unit  19  and video encoder  20  are illustrated as being separate units within video encoding unit  21  and video postprocessor unit  31  and video decoder  30  are illustrated as being separate units within video decoding unit  29 , the techniques described in this disclosure are not so limited. Video preprocessor unit  19  and video encoder  20  may be formed as a common device (e.g., integrated circuit or housed within the same chip). Similarly, video postprocessor unit  31  and video decoder  30  may be formed as a common device (e.g., integrated circuit or housed within the same chip). 
     In some examples, video encoder  20  and video decoder  30  may operate according to the High Efficiency Video Coding (HEVC) standard developed by the Joint Collaboration Team on Video Coding (JCT-VC) of ITU-T Video Coding Experts Group (VCEG) and ISO/IEC Motion Picture Experts Group (MPEG). A draft of the HEVC standard, referred to as the “HEVC draft specification” is described in Bross et al., “High Efficiency Video Coding (HEVC) Defect Report 3,” Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG11, 16 th  Meeting, San Jose, US, January 2014, document no. JCTVC-P1003_v1. The HEVC draft specification is available from http://phenix.it-sudparis.eu/jct/doc_end_user/documents/16_San %20Jose/wg11/JCTVC-P1003-v1.zip. The HEVC specification can also be accessed at http://www.itu.int/rec/T-REC-H.265-201504-I/en. 
     Furthermore, there are ongoing efforts to produce a scalable video coding extension for HEVC. The scalable video coding extension of HEVC may be referred to as SHEVC or SHVC. Additionally, a Joint Collaboration Team on 3D Video Coding (JCT-3C) of VCEG and MPEG is developing a 3DV standard based on HEVC. Part of the standardization efforts for the 3DV standard based on HEVC includes the standardization of a multi-view video codec based on HEVC (i.e., MV-HEVC). 
     In HEVC and other video coding specifications, a video sequence typically includes a series of pictures. Pictures may also be referred to as “frames.” A picture may include three sample arrays, denoted S L , S Cb , and S Cr . S L  is a two-dimensional array (i.e., a block) of luma samples. S Cb  is a two-dimensional array of Cb chrominance samples. S Cr  is a two-dimensional array of Cr chrominance samples. Chrominance samples may also be referred to herein as “chroma” samples. In other instances, a picture may be monochrome and may only include an array of luma samples. 
     To generate an encoded representation of a picture, video encoder  20  may generate a set of coding tree units (CTUs). Each of the CTUs may comprise a coding tree block of luma samples, two corresponding coding tree blocks of chroma samples, and syntax structures used to code the samples of the coding tree blocks. In monochrome pictures or pictures having three separate color planes, a CTU may comprise a single coding tree block and syntax structures used to code the samples of the coding tree block. A coding tree block may be an N×N block of samples. A CTU may also be referred to as a “tree block” or a “largest coding unit” (LCU). The CTUs of HEVC may be broadly analogous to the macroblocks of other standards, such as H.264/AVC. However, a CTU is not necessarily limited to a particular size and may include one or more coding units (CUs). A slice may include an integer number of CTUs ordered consecutively in a raster scan order. 
     This disclosure may use the term “video unit” or “video block” or “block” to refer to one or more sample blocks and syntax structures used to code samples of the one or more blocks of samples. Example types of video units may include CTUs, CUs, PUs, transform units (TUs), macroblocks, macroblock partitions, and so on. In some contexts, discussion of PUs may be interchanged with discussion of macroblocks or macroblock partitions. 
     To generate a coded CTU, video encoder  20  may recursively perform quad-tree partitioning on the coding tree blocks of a CTU to divide the coding tree blocks into coding blocks, hence the name “coding tree units.” A coding block is an N×N block of samples. A CU may comprise a coding block of luma samples and two corresponding coding blocks of chroma samples of a picture that has a luma sample array, a Cb sample array, and a Cr sample array, and syntax structures used to code the samples of the coding blocks. In monochrome pictures or pictures having three separate color planes, a CU may comprise a single coding block and syntax structures used to code the samples of the coding block. 
     Video encoder  20  may partition a coding block of a CU into one or more prediction blocks. A prediction block is a rectangular (i.e., square or non-square) block of samples on which the same prediction is applied. A prediction unit (PU) of a CU may comprise a prediction block of luma samples, two corresponding prediction blocks of chroma samples, and syntax structures used to predict the prediction blocks. In monochrome pictures or pictures having three separate color planes, a PU may comprise a single prediction block and syntax structures used to predict the prediction block. Video encoder  20  may generate predictive blocks (e.g., luma, Cb, and Cr predictive blocks) for prediction blocks (e.g., luma, Cb, and Cr prediction blocks) of each PU of the CU. 
     Video encoder  20  may use intra prediction or inter prediction to generate the predictive blocks for a PU. If video encoder  20  uses intra prediction to generate the predictive blocks of a PU, video encoder  20  may generate the predictive blocks of the PU based on decoded samples of the picture that includes the PU. 
     After video encoder  20  generates predictive blocks (e.g., luma, Cb, and Cr predictive blocks) for one or more PUs of a CU, video encoder  20  may generate one or more residual blocks for the CU. For instance, video encoder  20  may generate a luma residual block for the CU. Each sample in the CU&#39;s luma residual block indicates a difference between a luma sample in one of the CU&#39;s predictive luma blocks and a corresponding sample in the CU&#39;s original luma coding block. In addition, video encoder  20  may generate a Cb residual block for the CU. Each sample in the Cb residual block of a CU may indicate a difference between a Cb sample in one of the CU&#39;s predictive Cb blocks and a corresponding sample in the CU&#39;s original Cb coding block. Video encoder  20  may also generate a Cr residual block for the CU. Each sample in the CU&#39;s Cr residual block may indicate a difference between a Cr sample in one of the CU&#39;s predictive Cr blocks and a corresponding sample in the CU&#39;s original Cr coding block. 
     Furthermore, video encoder  20  may use quad-tree partitioning to decompose the residual blocks (e.g., the luma, Cb, and Cr residual blocks) of a CU into one or more transform blocks (e.g., luma, Cb, and Cr transform blocks). A transform block is a rectangular (e.g., square or non-square) block of samples on which the same transform is applied. A transform unit (TU) of a CU may comprise a transform block of luma samples, two corresponding transform blocks of chroma samples, and syntax structures used to transform the transform block samples. Thus, each TU of a CU may have a luma transform block, a Cb transform block, and a Cr transform block. The luma transform block of the TU may be a sub-block of the CU&#39;s luma residual block. The Cb transform block may be a sub-block of the CU&#39;s Cb residual block. The Cr transform block may be a sub-block of the CU&#39;s Cr residual block. In monochrome pictures or pictures having three separate color planes, a TU may comprise a single transform block and syntax structures used to transform the samples of the transform block. 
     Video encoder  20  may apply one or more transforms to a transform block of a TU to generate a coefficient block for the TU. For instance, video encoder  20  may apply one or more transforms to a luma transform block of a TU to generate a luma coefficient block for the TU. A coefficient block may be a two-dimensional array of transform coefficients. A transform coefficient may be a scalar quantity. Video encoder  20  may apply one or more transforms to a Cb transform block of a TU to generate a Cb coefficient block for the TU. Video encoder  20  may apply one or more transforms to a Cr transform block of a TU to generate a Cr coefficient block for the TU. 
     After generating a coefficient block (e.g., a luma coefficient block, a Cb coefficient block or a Cr coefficient block), video encoder  20  may quantize the coefficient block. Quantization generally refers to a process in which transform coefficients are quantized to possibly reduce the amount of data used to represent the transform coefficients, providing further compression. After video encoder  20  quantizes a coefficient block, video encoder  20  may entropy encode syntax elements indicating the quantized transform coefficients. For example, video encoder  20  may perform Context-Adaptive Binary Arithmetic Coding (CABAC) on the syntax elements indicating the quantized transform coefficients. 
     Video encoder  20  may output a bitstream that includes a sequence of bits that forms a representation of coded pictures and associated data. Thus, the bitstream comprises an encoded representation of video data. The bitstream may comprise a sequence of network abstraction layer (NAL) units. A NAL unit is a syntax structure containing an indication of the type of data in the NAL unit and bytes containing that data in the form of a raw byte sequence payload (RBSP) interspersed as necessary with emulation prevention bits. Each of the NAL units may include a NAL unit header and encapsulates a RBSP. The NAL unit header may include a syntax element indicating a NAL unit type code. The NAL unit type code specified by the NAL unit header of a NAL unit indicates the type of the NAL unit. A RBSP may be a syntax structure containing an integer number of bytes that is encapsulated within a NAL unit. In some instances, an RB SP includes zero bits. 
     Video decoder  30  may receive a bitstream generated by video encoder  20 . In addition, video decoder  30  may parse the bitstream to obtain syntax elements from the bitstream. Video decoder  30  may reconstruct the pictures of the video data based at least in part on the syntax elements obtained from the bitstream. The process to reconstruct the video data may be generally reciprocal to the process performed by video encoder  20 . For instance, video decoder  30  may use motion vectors of PUs to determine predictive blocks for the PUs of a current CU. In addition, video decoder  30  may inverse quantize coefficient blocks of TUs of the current CU. Video decoder  30  may perform inverse transforms on the coefficient blocks to reconstruct transform blocks of the TUs of the current CU. Video decoder  30  may reconstruct the coding blocks of the current CU by adding the samples of the predictive blocks for PUs of the current CU to corresponding samples of the transform blocks of the TUs of the current CU. By reconstructing the coding blocks for each CU of a picture, video decoder  30  may reconstruct the picture. 
     Aspects of HDR/WCG will now be discussed. Next generation video applications are anticipated to operate with video data representing captured scenery with HDR and WCG. Parameters of the utilized dynamic range and color gamut are two independent attributes of video content, and their specification for purposes of digital television and multimedia services are defined by several international standards. For example, Recommendation ITU-R BT. 709-5, “Parameter values for the HDTV standards for production and international programme exchange” (2002) (hereinafter, “ITU-R BT. Rec. 709”) defines parameters for HDTV (high definition television), such as Standard Dynamic Range (SDR) and standard color gamut. On the other hand, ITU-R Rec. 2020 specifies UHDTV (ultra-high definition television) parameters such as HDR and WCG. There are also other standards developing organization (SDOs) documents that specify dynamic range and color gamut attributes in other systems. For example, P3 color gamut is defined in SMPTE-231-2 (Society of Motion Picture and Television Engineers) and some parameters of HDR are defined in SMPTE ST 2084. A brief description of dynamic range and color gamut for video data is provided below. 
     Aspects of dynamic range will now be discussed. Dynamic range is typically defined as the ratio between the minimum and maximum brightness of the video signal. Dynamic range may also be measured in terms of ‘f-stop’ or “f-stops,” where one f-stop corresponds to a doubling of the signal dynamic range. In MPEG&#39;s definition, the HDR content is such content that features brightness variation with more than 16 f-stops. In some terms, levels between 10 and 16 f-stops are considered as intermediate dynamic range, but it is considered HDR in other definitions. At the same time, the human visual system (HVS) is capable of perceiving much a larger (e.g., “broader” or “wider”) dynamic range. However, the HVS includes an adaptation mechanism to narrow a so-called “simultaneous range.” 
       FIG. 2  is a conceptual diagram that illustrates visualization of dynamic range provided by SDR of HDTV, expected HDR of UHDTV and HVS dynamic range. For instance,  FIG. 2  illustrates Current video applications and services are regulated by ITU-R BT.709 and provide SDR. Current video applications and services typically support a range of brightness (or luminance) of around 0.1 to 100 candelas (cd) per meter-squared (m̂2) (units of cd/m̂2 are often referred to as “nits”), leading to fewer than or less than 10 f-stops. The next generation video services are expected to provide dynamic ranges of up-to 16 f-stops, and although detailed specifications are currently under development, some initial parameters have been specified in SMPTE ST 2084 and ITU-R BT.2020. 
     Color gamut will now be discussed. Another aspect for a more realistic video experience besides HDR is the color dimension, which is conventionally defined by the color gamut.  FIG. 3  is a conceptual diagram showing an SDR color gamut (triangle based on the ITU-R BT.709 color red, green and blue color primaries), and the wider color gamut for UHDTV (triangle based on the ITU-R BT.2020 color red, green and blue color primaries).  FIG. 3  also depicts the so-called spectrum locus (delimited by the tongue-shaped area), representing limits of the natural colors. As illustrated by  FIG. 3 , moving from ITU-R BT.709 to ITU-R BT.2020 color primaries aims to provide UHDTV services with about 70% more colors or greater colors. D65 specifies the white color for given specifications. 
     A few examples of color gamut specifications are shown in Table 1, below. 
     
       
         
           
               
             
               
                 TABLE 1 
               
             
            
               
                   
               
               
                 Color gamut parameters 
               
               
                 RGB color space parameters 
               
            
           
           
               
               
            
               
                   
                 Color space 
               
            
           
           
               
               
               
            
               
                   
                 White point 
                 Primary colors 
               
            
           
           
               
               
               
               
               
               
               
               
               
            
               
                   
                 xx W   
                 yy W   
                 xx R   
                 yy R   
                 xx G   
                 yy G   
                 xx B   
                 yy B   
               
               
                   
                   
               
            
           
           
               
               
               
               
               
               
               
               
               
            
               
                 DCI-P3 
                 0.314 
                 0.351 
                 0.680 
                 0.320 
                 0.265 
                 0.690 
                 0.150 
                 0.060 
               
               
                 ITU-R 
                 0.3127 
                 0.3290 
                 0.64 
                 0.33 
                 0.30 
                 0.60 
                 0.15 
                 0.06 
               
               
                 BT.709 
               
               
                 ITU-R 
                 0.3127 
                 0.3290 
                 0.708 
                 0.292 
                 0.170 
                 0.797 
                 0.131 
                 0.046 
               
               
                 BT.2020 
               
               
                   
               
            
           
         
       
     
     Aspects of representations of HDR video data will now be discussed. HDR/WCG is typically acquired and stored at a very high precision per component (even floating point), with the 4:4:4 chroma format and a very wide color space (e.g., XYZ). CIE 1931, set forth by the International Commission on Illumination, is an example of the XYZ color space. This representation targets high precision and is (almost) mathematically lossless. However, this format feature may include a lot of redundancies and is not optimal for compression purposes. A lower precision format with HVS-based assumption is typically utilized for state-of-the-art video applications. 
     One example of a video data format conversion process for purposes of compression includes three major processes, as shown by conversion process  109  of  FIG. 4 . The techniques of  FIG. 4  may be performed by source device  12 . Linear RGB data  110  may be HDR/WCG video data and may be stored in a floating point representation. Linear RGB data  110  may be compacted using a non-linear transfer function (TF)  112  for dynamic range compacting. Transfer function  112  may compact linear RGB data  110  using any number of non-linear transfer functions, e.g., the PQ TF as defined in SMPTE-2084. In some examples, color conversion process  114  converts the compacted data into a more compact or robust color space (e.g., a YUV or YCrCb color space) that is more suitable for compression by a hybrid video encoder. This data is then quantized using a floating-to-integer representation quantization unit  116  to produce converted HDR′ data  118 . In this example HDR′ data  118  is in an integer representation. The HDR′ data is now in a format more suitable for compression by a hybrid video encoder (e.g., video encoder  20  applying HEVC techniques). The order of the processes depicted in  FIG. 4  is given as an example, and may vary in other applications. For example, color conversion may precede the TF process. In addition, additional processing, e.g. spatial subsampling, may be applied to color components. 
     An example inverse conversion at the decoder side is depicted in  FIG. 5 , by way of process  129 . Video postprocessor unit  31  of destination device  14  may perform the techniques of  FIG. 5 . Converted HDR′ data  120  may be obtained at destination device  14  through decoding video data using a hybrid video decoder (e.g., video decoder  30  applying HEVC techniques). HDR′ data  120  may then be inverse quantized by inverse quantization unit  122 . Then an inverse color conversion process  124  may be applied to the inverse quantized HDR′ data. The inverse color conversion process  124  may be the inverse of color conversion process  114 . For example, the inverse color conversion process  124  may convert the HDR′ data from a YCrCb format back to an RGB format. Next, inverse transfer function  126  may be applied to the data to add back the dynamic range that was compacted by transfer function  112  to recreate the linear RGB data  128 . The high dynamic range of input RGB data in linear and floating point representation is compacted with the utilized non-linear transfer function (TF). For instance, the perceptual quantizer (PQ) TF as defined in SMPTE ST 2084, following which it is converted to a target color space more suitable for compression, e.g. Y′CbCr, and then quantized to achieve integer representation. The order of these elements is given as an example, and may vary in real-world applications, e.g., color conversion may precede the TF module, as well as additional processing, e.g., spatial subsampling may be applied to color components. These three components are described in greater detail below. 
     Certain aspects depicted in  FIG. 4  will now be discussed in more detail, such as the transfer function (TF). Mapping the digital values appearing in an image container to and from optical energy may require knowledge of the TF. A TF is applied to the data to compact the data&#39;s dynamic range and make it possible to represent the data with limited number of bits. This function is typically a one-dimensional (1D) non-linear function either reflecting an inverse of electro-optical transfer function (EOTF) of the end-user display as specified for SDR in ITU-R BT.  1886  and Rec.  709  or approximating the HVS perception to brightness changes as for PQ TF specified in SMPTE ST 2084 for HDR. The inverse process of the OETF is the EOTF (electro-optical transfer function), which maps the code levels back to luminance.  FIG. 6  shows several examples of TFs. These mappings may also be applied to each R, G, and B component separately. Applying these mappings to the R, G, and B components may convert them to R′, G′, and B′, respectively. 
     The reference EOTF specified in ITU-R recommendation BT.1886 is specified by the following equation: 
         L=a (max[( V+b ),0]) γ   
     where:
         L: Screen luminance in cd/m̂2   L W : Screen luminance for white   L B : Screen luminance for black   V: Input video signal level (normalized, black at V=0, to white at V=1. For content mastered per Recommendation ITU-R BT.709, 10-bit digital code values “D” map into values of V per the following equation: V=(D-64)/876   γ: Exponent of power function, γ=2.404   a: Variable for user gain (legacy “contrast” control)       

         a =( L   W   1/γ   −L   B   1/γ ) γ           b: Variable for user black level lift (legacy “brightness” control)       
     
       
         
           
             b 
             = 
             
               
                 L 
                 B 
                 
                   1 
                   / 
                   γ 
                 
               
               
                 
                   L 
                   W 
                   
                     1 
                     / 
                     γ 
                   
                 
                 - 
                 
                   L 
                   B 
                   
                     1 
                     / 
                     γ 
                   
                 
               
             
           
         
       
     
     Above variables a and b are derived by solving following equations in order that V=1 gives 
     L=L W  and that V=0 gives L=L B : 
     
       
      
       L 
       B 
       =a·b 
       γ 
      
     
         L   W   =a ·(1+ b ) γ 
 
     In order to support higher dynamic range data more efficiency, SMPTE has recently standardized a new transfer function called SMPTE ST-2084. A specification of ST2084 defined the EOTF application as described as follows. A TF is applied to normalized linear R, G, B values, which results in nonlinear representation of R′, G′, B′. ST2084 defines normalization by NORM=10000, which is associated with a peak brightness of 10000 nits (cd/m̂2). 
     
       
         
           
             
               
                 
                   
                     
                       
                         
                           
                             
                               
                                 
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                     = 
                     
                       
                         
                           2610 
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                       = 
                       0.1593017578125 
                     
                   
                    
                   
                     
 
                   
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                       m 
                       2 
                     
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                           2523 
                           4096 
                         
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                       = 
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                    
                   
                     
 
                   
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                       c 
                       1 
                     
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                   ( 
                   1 
                   ) 
                 
               
             
           
         
       
     
     Typically, EOTF is defined as a function with a floating point accuracy. Thus, no error is introduced to a signal with this non-linearity if inverse TF (a so-called OETF) is applied. Inverse TF (OETF) as specified in ST2084 is defined using an inverse PQ function as follows: 
     
       
         
           
             
               
                 
                   
                     
                       
                         
                           
                             
                               R 
                               = 
                               
                                 10000 
                                 * 
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                    
                   
                     
 
                   
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                   ( 
                   2 
                   ) 
                 
               
             
           
         
       
     
     EOTF and OETF are subjects of active research and standardization, and a TF utilized in some video coding systems may be different from the TF as specified in ST2084. 
     Color Transform will now be discussed. RGB data is typically used as input, because RGB data is often produced by image capturing sensors. However, this color space has high redundancy among its components and is not optimal for compact representation. To achieve a more compact and more robust representation, RGB components are typically converted to a more uncorrelated color space (i.e., a color transform is performed) that is more suitable for compression, e.g., YCbCr. This color space separates the brightness in the form of luminance and color information in different un-correlated components. 
     For modern video coding systems, a commonly-used or typically-used color space is YCbCr, as specified in ITU-R BT.709. The YCbCr color space in the BT.709 standard specifies the following conversion process from R′G′B′ to Y′CbCr (non-constant luminance representation): 
     
       
         
           
             
               
                 
                   
                     
                       Y 
                       ′ 
                     
                     = 
                     
                       
                         0.2126 
                         * 
                         
                           R 
                           ′ 
                         
                       
                       + 
                       
                         0.7152 
                         * 
                         
                           G 
                           ′ 
                         
                       
                       + 
                       
                         0.0722 
                         * 
                         
                           B 
                           ′ 
                         
                       
                     
                   
                    
                   
                     
 
                   
                    
                   
                     Cb 
                     = 
                     
                       
                         
                           B 
                           ′ 
                         
                         - 
                         
                           Y 
                           ′ 
                         
                       
                       1.8556 
                     
                   
                    
                   
                     
 
                   
                    
                   
                     Cr 
                     = 
                     
                       
                         
                           R 
                           ′ 
                         
                         - 
                         
                           Y 
                           ′ 
                         
                       
                       1.5748 
                     
                   
                 
               
               
                 
                   ( 
                   3 
                   ) 
                 
               
             
           
         
       
     
     The above can also be implemented using the following approximate conversion that avoids the division for the Cb and Cr components: 
         Y′= 0.212600* R′+ 0.715200* G′+ 0.072200* B′   
         Cb=− 0.114572* R′− 0.385428* G′+ 0.500000* B′   (4)
 
         Cr= 0.500000* R′− 0.454153* G′− 0.045847* B′   
     The ITU-R BT.2020 standard specifies two different conversion processes from RGB to Y′CbCr: Constant-luminance (CL) and Non-constant luminance (NCL), Recommendation ITU-R BT. 2020, “Parameter values for ultra-high definition television systems for production and international programme exchange” (2012). The RGB data may be in linear light and Y′CbCr data is non-linear.  FIG. 7  is a block diagram illustrating an example for non-constant luminance. Particularly,  FIG. 7  shows an example of an NCL approach, by way of process  131 . The NCL approach of  FIG. 7  applies the conversion from R′G′B′ to Y′CbCr ( 136 ) after OETF ( 134 ). The ITU-R BT.2020 standard specifies the following conversion process from R′G′B′ to Y′CbCr (non-constant luminance representation): 
     
       
         
           
             
               
                 
                   
                     
                       Y 
                       ′ 
                     
                     = 
                     
                       
                         0.2627 
                         * 
                         
                           R 
                           ′ 
                         
                       
                       + 
                       
                         0.6780 
                         * 
                         
                           G 
                           ′ 
                         
                       
                       + 
                       
                         0.0593 
                         * 
                         
                           B 
                           ′ 
                         
                       
                     
                   
                    
                   
                     
 
                   
                    
                   
                     Cb 
                     = 
                     
                       
                         
                           B 
                           ′ 
                         
                         - 
                         
                           Y 
                           ′ 
                         
                       
                       1.8814 
                     
                   
                    
                   
                     
 
                   
                    
                   
                     Cr 
                     = 
                     
                       
                         
                           R 
                           ′ 
                         
                         - 
                         
                           Y 
                           ′ 
                         
                       
                       1.4746 
                     
                   
                 
               
               
                 
                   ( 
                   5 
                   ) 
                 
               
             
           
         
       
     
     The above can also be implemented using the following approximate conversion that avoids the division for the Cb and Cr components, as described in the following equation(s): 
         Y′= 0.262700* R′+ 0.678000* G+ 0.059300* B′   
         Cb=− 0.139630* R′− 0.360370* G′+ 0.500000* B′   (6)
 
         Cr= 0.500000* R′− 0.459786* G′− 0.040214* B′   
     Quantization/Fix point conversion will now be discussed. Following the color transform, input data in a target color space still represented at high bit-depth (e.g., floating point accuracy) is converted to a target bit-depth. Certain studies show that ten-to-twelve (10-12) bits accuracy in combination with the PQ TF is sufficient to provide HDR data of 16 f-stops with distortion below the Just-Noticeable Difference (JND). Data represented with 10-bit accuracy can be further coded with most of the state-of-the-art video coding solutions. This quantization ( 138 ) is an element of lossy coding and may be a source of inaccuracy introduced to converted data. 
     In various examples, such quantization may be applied to code words in a target color space. An example in which YCbCr is applied is shown below. Input values YCbCr represented in floating point accuracy are converted into a signal of fixed bit-depth BitDepthY for the luma (Y) value and BitDepthC for the chroma values (Cb, Cr). 
         D   Y′ =Clip1 Y (Round((1&lt;&lt;(BitDepth Y −8))*(219* Y′+ 16)))
 
         D   Cb =Clip1 C (Round((1&lt;&lt;(BitDepth C −8))*(224* Cb+ 128)))  (7)
 
         D   Cr =Clip1 C (Round((1&lt;&lt;(BitDepth C −8))*(224* Cr+ 128)))
 
     with
         Round(x)=Sign(x)*Floor(Abs(x)+0.5)   Sign(x)=−1 if x&lt;0, 0 if x=0, 1 if x&gt;0   Floor(x) the largest integer less than or equal to x   Abs(x)=x if x&gt;=0, −x if x&lt;0   Clip 1   Y (x)=Clip 3 (0, (1&lt;&lt;BitDepth Y )−1, x)   Clip 1   C (x)=Clip 3 (0, (1&lt;&lt;BitDepth C )−1, x)   Clip 3 ( x,y,z )=x if z&lt;x, y if z&gt;y, z otherwise       

     Some of the transfer functions and color transforms may result in video data representation that features significant variation of a Just-Noticeable Difference (JND) threshold value over the dynamic range of the signal representation. For such representations, a quantization scheme that is uniform over the dynamic range of luma values would introduce quantization error with different merit of perception over the signal fragments (which represent partitions of dynamical range). Such impact on signals may be interpreted as a processing system with a non-uniform quantization which results in unequal signal-to-noise ratios within processed data range. Process  131  of  FIG. 7  also includes a conversion from 4:4:4 to 4:2:0 ( 140 ) and HEVC 4:2:0 10b encoding ( 142 ). 
     An example of such a representation is a video signal represented in a Non Constant Luminance (NCL) YCbCr color space, for which color primaries are defined in ITU-R Rec. BT.2020 and with an ST 2084 transfer function. As illustrated in Table 2 below, this representation (e.g., the video signal represented in the NCL YCbCr color space) allocates a significantly larger amount of codewords for the low intensity values of the signal. For instance, 30% of the codewords represent linear light samples below ten nits (&lt;10 nits). In contrast, high intensity samples (high brightness) are represented with an appreciably smaller amount of codewords. For instance, 25% of the codewords are allocated for linear light in the range 1000-10,000 nits. As a result, a video coding system, such as an H.265/HEVC video coding system, featuring uniform quantization for all ranges of the data, would introduce much more severe coding artifacts to the high intensity samples (bright region of the signal), whereas the distortion introduced to low intensity samples (dark region of the same signal) would be far below a noticeable difference. 
     Effectively, the factors described above may mean that video coding system design, or encoding algorithms, may need to be adjusted for every selected video data representation, namely for every selected transfer function and color space. Because of codeword differences, the SDR coding devices may not be optimized for HDR content. Also, a significant amount of video content has been captured in the SDR dynamic range and SCG colors (provided by Rec. 709). As compared to HDR and WCG, the SDR-SCG video capture provides a narrow range. As such, the SDR-SCG captured video data may occupy a relatively small the footprint of a codeword scheme with respect to HDR-WCG video data. To illustrate, the SCG of Rec. 709 covers 35.9% of the CIE 1931 color space, while WCG of the Rec. 2020 covers 75.8%. 
     
       
         
           
               
             
               
                 TABLE 2 
               
             
            
               
                   
               
               
                 Relation between linear light intensity and 
               
               
                 code value in SMPTE ST 2084 (bit depth = 10) 
               
            
           
           
               
               
               
               
            
               
                 Linear light intensity (cd/m 2 ) 
                 Full range 
                 SDI range 
                 Narrow range 
               
               
                   
               
            
           
           
               
               
               
               
            
               
                 ~0.01 
                 21 
                 25 
                 83 
               
               
                 ~0.1 
                 64 
                 67 
                 119 
               
               
                 ~1 
                 153 
                 156 
                 195 
               
               
                 ~10 
                 307 
                 308 
                 327 
               
               
                 ~100 
                 520 
                 520 
                 509 
               
               
                 ~1,000 
                 769 
                 767 
                 723 
               
               
                 ~4,000 
                 923 
                 920 
                 855 
               
               
                 ~10,000 
                 1023 
                 1019 
                 940 
               
               
                   
               
            
           
         
       
     
     As shown in Table 2 above, a high concentration of the codewords (shown in the “full range” column) are concentrated in a low-brightness range. That is, a total 307 codewords (which constitute approximately 30% of the codewords) are clustered within the 0-10 nits range of linear light intensity. In low-brightness scenarios, color information may not be easily perceptible, and may be visible at low levels of visual sensitivity. Because of the concentrated clustering of codewords being positioned in the low-brightness range, a video encoding device may encode a significant amount of, in high quality or very high quality, in the low-brightness range. Moreover, the bitstream may consume greater amounts of bandwidth in order to convey the encoded noise. A video decoding device, when reconstructing the bitstream, may produce a greater number of artifacts, due to the encoded noise being included in the bitstream. 
     Existing proposals to improve non-optimal perceptual quality codeword distribution are discussed below. One such proposal is “Dynamic Range Adjustment SEI to enable High Dynamic Range video coding with Backward-Compatible Capability,” by D. Rusanovskyy, A. K. Ramasubramonian, D. Bugdayci, S. Lee, J. Sole, M. Karczewicz, VCEG document COM16-C 1027-E, September2015 (hereinafter “Rusanovskyy I”). Rusanovskyy I included a proposal to apply a codewords re-distribution to video data prior to video coding. According to this proposal, video data in the ST 2084/BT.2020 representation undergoes a codeword re-distribution prior to video compression. This proposal introduced re-distribution introduce linearization of perceived distortion (signal to noise ratio) within a dynamical range of the data through a Dynamical Range Adjustment. This redistribution was found to improve visual quality under the bitrate constrains. To compensate the redistribution and convert data to the original ST 2084/BT.2020 representation an inverse process is applied to the data after video decoding. The techniques proposed by Rusanovskyy I are further described further in U.S. patent application Ser. No. 15/099,256 (claiming priority to provisional patent application No. 62/149,446) and U.S. patent application Ser. No. 15/176,034 (claiming priority to provisional patent application No. 62/184,216), the entire content of each of which is incorporated herein in its entirety. 
     However, according to the techniques described in Rusanovskyy I, the processes of pre- and post-processing are generally de-coupled from rate distortion optimization processing employed by state-of-the-art encoders at the block-based basis. Therefore, the described techniques are from the point of view of pre-processing and post-processing, which are outside of (or external to) the coding loop of a video codec. 
     Another such proposal is “Performance investigation of high dynamic range and wide color gamut video coding techniques,” by J. Zhao, S.-H. Kim, A. Segall, K. Misra, VCEG document COM16-C 1030-E, September2015 (hereinafter “Zhao I”). Zhao proposed an intensity dependent spatially varying (block based) quantization scheme to align bitrate allocation and visually-perceived distortion between video coding applied on Y2020 (ST2084/BT2020) and Y709 (BT1886/BT 2020) representations. It was observed that to maintain the same level of quantization in luma, the quantization of signal in Y2020 and Y709 must differ by a value that depends on luma, such that: 
       QP_ Y 2020=QP_ Y 709− f ( Y 2020)
 
     The function f (Y2020) was found to be linear for intensity values (brightness level) of video in Y2020, and it may be approximated as: 
         f ( Y 2020)=max(0.03* Y 2020−3,0)
 
     Zhao I proposed spatially varying quantization scheme being introduced at the encoding stage was found to be able to improve visually perceived signal-to-quantization noise ratio for coded video signal in ST 2084/BT.2020 representation. 
     A potential drawback of the techniques proposed in Zhao I is a block-based granularity of QP adaptation. Typically, utilized block sizes selected at the encoder side for compression are derived through a rate distortion optimization process, and may not represent dynamical range properties of the video signal. Thus, the selected QP settings may be sub-optimal for the signal inside of the block. This potential problem may become even more important for the next generation of video coding systems that tend to employ prediction and transform block sizes of larger dimensions. Another aspect of this design is a need for signaling of QP adaptation parameters. QP adaptation parameters are signaled to the decoder for inverse dequantization. Additionally, spatial adaptation of quantization parameters at the encoder side may increase the complexity of encoding optimization and may interfere with rate control algorithms. 
     Another such proposal is “Intensity dependent spatial quantization with application in HEVC,” by Matteo Naccari and Marta Mrak, In Proc. of IEEE ICME 2013, July 2013 (hereinafter “Naccari”). Naccari proposed an Intensity Dependent Spatial Quantization (IDSQ) perceptual mechanism, which exploits the intensity masking of the human visual system and perceptually adjusts quantization of the signal at the block level. This paper proposed employing in-loop pixel domain scaling. According to this proposal, parameters of in-loop scaling for a currently-processed block are derived from average values of luma component in the predicted block. At the decoder side, the inverse scaling is performed, and the decoder derives parameters of scaling from the predicted block available at the decoder side. 
     Similarly to the work in Zhao I discussed above, a block-based granularity of this approach restricts the performance of this method due sub-optimality of scaling parameter which is applied to all samples of the processed block. Another aspect of the proposed solution of this paper is that the scale value is derived from predicted block and does not reflect signal fluctuation which may happen between a current codec block and a predicted block. 
     Another such proposal is “De-quantization and scaling for next generation containers,” by J. Zhao, A. Segall, S.-H. Kim, K. Misra, JVET document B0054, January 2016 (hereinafter Zhao II″). To improve non-uniform perceived distortion in the ST 2084/BT2020 representation, this paper proposed employing in-loop intensity dependent block based transform domain scaling. According to this proposal, parameters of in-loop scaling for selected transform coefficients (AC coefficients) of the currently processed block are derived as a function of average values of a luma component in the predicted block and DC value derived for the current block. At the decoder side, the inverse scaling is performed, and the decoder derives parameters of AC coefficient scaling from predicted block available at the decoder side and from quantized DC value which is signalled to the decoder. 
     Similarly to works in Zhao I and Naccari discussed above, a block-based granularity of this approach restricts the performance of this method due sub-optimality of scaling parameter which is applied to all samples of the processed block. Another aspect of this paper&#39;s proposed scheme is that the scale value is applied to AC transform coefficients only, therefor signal-to-noise ratio improvement does not affect the DC value, which reduces the performance of the scheme. In addition to the aspects discussed above, in some video coding system designs, a quantized DC value may not be available at the time of AC values scaling, such as in a case where the quantization process follows a cascade of transform operations. Another restriction of this proposal is that when the encoder selects the transform skip or transform/quantization bypass modes for the current block, scaling is not applied (hence, at the decoder, scaling is not defined for transform skip and transform/quantization bypass modes) which is sub-optimal due to exclusion of potential coding gain for these two modes. 
     In U.S. patent application Ser. No. 15/595,793 (claiming priority to provisional patent application No. 62/337,303) by Dmytro Rusanovskyy et al. (hereinafter “Rusanovskyy II”), in-loop sample processing for video signals with non-uniformly distributed Just Noticeable Difference (JND). According to the techniques of Rusanovskyy II, several in-loop coding approaches for more efficient coding of signals with non-uniformly distributed Just Noticeable Difference. Rusanovskyy II describes application of scale and offset of signal samples represented either in pixel, residual or transform domain. Several algorithms for derivation of the scale and offset has been proposed. The content of Rusanovskyy II is incorporated by reference herein in its entirety. 
     This disclosure discusses several devices, components, apparatuses, and methods for processing that can be applied in the loop of the video coding system. The techniques of this disclosure may include processes of quantization and/or scaling of a video signal in the pixel domain or in a transform domain to improve signal-to-quantization noise ratios for the processed data. For instance, the systems and techniques of this disclosure may reduce artifacts caused by conversion of video data captured in SDR-SCG format when converted to HDR-WCG format. Techniques described herein may address precision using one or both of luminance and/or chrominance data. The disclosed systems and techniques also incorporate or include several algorithms for derivation of quantization or scaling parameters from a spatio-temporal neighborhood of the signal. That is, example systems and techniques of this disclosure are directed to obtaining one or more parameter values that are used to modify residual data associated with the current block in a coding process. As used herein, a parameter value that is used to modify residual data may include a quantization parameter (used to modify the residual data by quantizing or dequantizing residual data in an encoding process or decoding process, respectively), or a scaling parameter (used to modify the residual data by scaling or inverse-scaling residual data in an encoding process or decoding process, respectively). 
       FIG. 8  is a conceptual diagram illustrating aspects of a spatio-temporal neighborhood of a currently-coded block  152 . According to one or more techniques of this disclosure, video encoder  20  may derive quantization parameters (to be used in the quantization of samples of currently-coded block  152 ) using information from the spatio-temporal neighborhood of currently-coded block  152 . For instance, video encoder  20  may derive a reference QP or a default QP for use with currently-coded block  152  using QP values used for one or more of neighboring blocks  154 ,  156 , and  158 . For example, video encoder  20  may use the QP values for one or more of neighboring blocks  154 - 158  as criteria or operands in a delta QP derivation process with respect to currently-coded block  152 . In this way, video encoder  20  may implement one or more techniques of this disclosure to consider samples of left neighbor block  156 , samples of top neighbor block  158 , and samples of a temporal neighbor block  154 , which is pointed to by a disparity vector “DV.” 
     As such, video encoder  20  may implement the techniques of this disclosure to expand the delta QP derivation process for currently-coded block  152  to base the delta QP derivation process at least partially on various neighboring blocks of the spatio-temporal neighborhood, if video encoder  20  determines that samples of spatio-temporal neighboring blocks are a good match for the samples of currently-coded block  152 . In instances where a block of reference samples overlaps with multiple CUs of the block partitioning, and thus can have different QP, video encoder  20  may derive the QP from a multitude of the available QPs. For instance, video encoder  20  may implement a process of averaging with respect to the multiple QP values, to derive the QP value for the samples of currently-coded block  152 . In various examples, video encoder  20  may implement the derivation techniques described above to derive one or both of a QP value and/or delta QP parameters. 
     In various use-case scenarios, video encoder  20  may also derive scaling parameters for the samples of currently-coded block  152  using information from the spatio-temporal neighborhood of currently-coded block  152 . For example, in accordance with designs where a scaling operation replaces uniform quantization, video encoder  20  may apply the spatio-temporal neighborhood-based derivation process described above to derive reference scaling parameters or default scaling parameters for currently-coded block  152 . 
     According to some existing HEVC/JEM techniques, a video coding device may apply scaling operations to all transform coefficients of a currently-processed block. For instance, in some HEVC/JEM designs, a video coding device may apply one or more scaling parameters to a sub-set of transform coefficients, while utilizing the remaining transform coefficients for the derivation of the scaling parameter(s). For instance, according to JVET B0054, a video coding device may derive in-loop scaling parameters for selected transform coefficients (namely, AC coefficients) of the currently-processed block as a function of average values of the luma component in the predicted block, and may derive the DC value for the current block. 
     According to one or more techniques of this disclosure, video encoder  20  may include one or more DC transform coefficients in the scaling process for currently-coded block  152 . In some examples, video encoder  20  may derive the scaling parameters for currently-coded block  152  as a function of a DC value and parameters derived from predicted samples. Video encoder  20  may implement a scaling parameter derivation process that includes a look-up table (LUT) for AC scaling, as well as an independent LUT for DC value(s). Forward scaling of DC and AC transform coefficients results in scaled values denoted as DC′ and AC′. Video encoder  20  may implement scaling operations as described below to obtain the scaled values DC′ and AC′: 
       AC′=scale(fun1(DC,avgPred))*AC; and
 
       DC′=scale(fun2(DC,avgPred))*DC
 
     In accordance with the scaling parameter-based techniques of this disclosure, video decoder  30  may implement generally reciprocal operations to those described above with respect to video encoder  20 . For instance, video decoder  30  may implement an inverse scaling process that uses the scaled values DC′ and AC′ as operands. The results of the inverse scaling process are denoted as DC″ and AC″ in the equations below. Video decoder  30  may implement the inverse scaling operations as illustrated in the following equations: 
       DC″=DC′/scale(fun1(DC′,avgPred)); and
 
       AC″=AC′/scale(fun2(DC″,avgPred))
 
     With respect to both the scaling and the inverse scaling operations, the terms ‘fun 1 ’ and ‘fun 2 ’ define scale derivation functions/processes that use, as arguments, an average of reference samples and DC-based values. As illustrated with respect to both the scaling and the inverse scaling techniques implemented by video encoder  20  and video decoder  30 , the techniques of this disclosure enable the use of DC transform coefficient values in the derivation of both the scaled and inverse-scaled DC and AC transform coefficient values. In this way, techniques of this disclosure enable video encoder  20  and video decoder  30  to leverage DC transform coefficient values in scaling and inverse-scaling operations, if the scaling/inverse-scaling operations are performed in place of quantization and dequantization of transform coefficients. 
     This disclosure also provides techniques for derivation of quantization parameters or scaling parameters in instances where video encoder  20  does not signal any non-zero transform coefficients. The current specification of HEVC, the initial test model of JVET development, and the design described in JVET B0054 specify derivation of QP values (or scaling parameters, as the case may be) as a function of encoded non-zero transform coefficients that are present. In a case where all transform coefficients are quantized to zero, no QP adjustment nor locally-applied scale are signaled, according to the current specification of HEVC, the initial test model of JVET, and the design of JVET B0054. Instead, the decoding device applies, to the transform coefficients, either a global (e.g., slice level) QP/scaling parameter, or a QP which is derived from spatial neighboring CUs. 
     Techniques of this disclosure leverage the relative accuracy of prediction (whether intra or inter) which results in the absence of non-zero transform coefficients. For instance, video decoder  30  may implement the techniques of this disclosure to use parameters from predicted samples to derive QP values or scaling parameters. In turn, video decoder  30  may utilize the derived QP values or scaling parameters to dequantize the samples of a current block or to inverse-scale the transform coefficients of the current block. In this way, video decoder  30  may implement techniques of this disclosure to leverage the prediction accuracy in scenarios in which video decoder  30  receives no non-zero transform coefficients for a block, thereby replacing one or more default-based dequantization and inverse-scaling aspects of the HEVC/JEM practices. 
     Various example implementations of the disclosed techniques are described below. It will be understood that the implementations described below are non-limiting examples, and that other implementations of the disclosed techniques are also possible in accordance with aspects of this disclosure. 
     According to some implementations, video encoder  20  may derive a reference QP value from attached (top and left) blocks (CUs). Described with respect to  FIG. 8 , video encoder  20  may derive the reference QP for currently-coded block  152  from data associated with top neighbor block  158  and left neighbor block  156 . An example of this example implementation is described by the pseudocode below: 
                                            Char TComDataCU::getRefQP( UInt uiCurrAbsIdxInCtu )           {              TComDataCU* cULeft = getQpMinCuLeft ( lPartIdx,           m_absZIdxInCtu + uiCurrAbsIdxInCtu );              TComDataCU* cUAbove = getQpMinCuAbove( aPartIdx,           m_absZIdxInCtu + uiCurrAbsIdxInCtu );              return (((cULeft? cULeft-&gt;getQP( lPartIdx ):           m_QuLastCodedQP) + (cUAbove? cUAbove-&gt;getQP( aPartIdx ):           m_QuLastCodedQP) + 1) &gt;&gt; 1);           }                        
In the pseudocode above, the attached blocks are represented by the symbols “cUAbove” and “cULeft.”
 
     According to some implementations of the techniques of this disclosure, video encoder  20  may take one or more QP values of reference sample(s) into consideration in the QP derivation process. An example of such an implementation is described by the pseudocode below: 
                                            Char TComDataCU::getRefQP2( UInt uiCurrAbsIdxInCtu )           {              TComDataCU* cULeft = getQpMinCuLeft ( lPartIdx,           m_absZIdxInCtu + uiCurrAbsIdxInCtu );              TComDataCU* cUAbove = getQpMinCuAbove( aPartIdx,           m_absZIdxInCtu + uiCurrAbsIdxInCtu );              TComDataCU* cURefer = getQpMinCuReference( aPartIdx,           m_absZIdxInCtu + uiCurrAbsIdxInCtu );              return value = function (cULeft-&gt;getLastQP( ),           cUAbove-&gt;getLastQP( ), cURefer -&gt;getLastQP( ));           }                        
In the pseudocode above, the symbol “cURefer” represents a block that includes reference samples.
 
     According to some implementations of the described techniques, video encoder  20  and/or video decoder  30  may store QPs applied on samples of reference block(s) and/or global QPs (e.g., slice-level QPs) for all pictures utilized as reference pictures. According to some implementations, video encoder  20  and/or video decoder  30  may store scaling parameters applied on samples of reference block(s) and/or global scaling (e.g., slice-level scaling) parameters for all pictures utilized as reference pictures. If a block of reference samples overlaps with multiple CUs of the partitioned block (and thus introducing the possibility of different QPs across the partitions), video encoder  20  may derive the QP from a multitude of the available QPs. As an example, video encoder  20  may implement an averaging process on the multiple QPs from the multiple CUs. An example of such an implementation is described by the pseudocode below: 
                                            Int sum= 0;            for (Int i=0; i &lt; numMinPart; i++)            {               sum +=               m_phInferQP[COMPONENT_Y][uiAbsPartIdxInCTU + i];            }            avgQP = (sum)/numMinPart;                        
According to the pseudocode above, video encoder  20  performs the averaging processing by calculating a mean value of the QPs across the block partitions. The mean QP calculation is shown in the last operation in the pseudocode above. That is, video encoder  20  divides an aggregate (represented by the final value of the integer “sum”) divided by a count of partitions (represented by the operand “numMinPart”).
 
     In yet another implementation of the techniques described herein, video encoder  20  may derive the QP as a function of the average brightness of luma components. For instance, video encoder  20  may obtain the average brightness of the luma components from a lookup table (LUT). This implementation is described by the following pseudocode, where the symbol “avgPred” represents an average brightness value of the reference samples: 
       QP=PQ_LUT[avgPred]; 
     In some implementations, video encoder  20  may derive a reference QP value for a current block from one or more global QP values. An example of a global QP value that video encoder  20  may use is a QP specified at the slice level. That is, video encoder  20  may derive the QP value for the current block using a QP value specified for an entirety of a slice that includes the current block. This implementation is described by the following pseudocode: 
       qp=(((Int)pcCU−&gt;getSlice( )&gt;getSliceQp( )+ iD Qp+52+2*qp Bd Offset Y )%(52+qp Bd Offset Y ))−qp Bd Offset Y;  
 
     In the pseudocode above, video encoder  20  uses the value returned by the getSliceQp( ) function as an operand in the operation to obtain the QP for the current block (denoted by “qp”). 
     In some implementations of the techniques described herein, video encoder  20  may utilize one or more reference sample values in deriving QPs. This implementation is described by the following pseudocode: 
       QP=PQ_LUT[avgPred]; 
     In the pseudocode above, “PQ_LUT” is a look up table which video encoder  20  may utilize to map an average brightness of the predicted block (represented by “avgPred”) value to an associated perceptual quantizer (PQ) value. Video encoder  20  may compute the value of avgPred as a function of reference samples, such as an average value of the reference samples. Examples of average values that can be used in accordance with the calculations of this disclosure include one or more of mean, median, and mode values. 
     In some implementations, video encoder  20  may scaling parameters for the current block instead of QPs. In some implementations, video encoder  20  may perform a conversion process from the derived QP(s) to scale parameter(s), or vice versa. In some implementations, video encoder  20  may utilize an analytical expression to derive a QP from reference samples. One example of an analytical expression that video encoder  20  may use for QP derivation is a parametric derivation model. 
     Regardless of which of the above-described techniques that video encoder  20  derives the QP for the current block, video encoder  20  may signal data based on the derived QP to video decoder  30 . For instance, video encoder  20  may signal a delta QP value derived from the QP value that video encoder  20  used to quantize the samples current block. In turn, video decoder  30  may use the delta QP value received in the encoded video bitstream to obtain the QP value for the block, and may dequantize the samples of the block using the QP value. 
     In examples in which video encoder  20  obtains scaling parameters instead of or in addition to the QP value for the current block, video encoder  20  may signal the scaling parameters (or data derived therefrom) to video decoder  30 . In turn, video decoder  30  may reconstruct the scaling parameters, either directly or by deriving the parameters from the signaled data, from the encoded video bitstream. Video decoder  30  may perform inverse scaling of the scaled transform coefficients. For instance, video decoder  30  may perform inverse scaling of scaled versions of both DC and AC transform coefficients, in accordance with aspects of this disclosure. 
     Various examples (e.g., implementations) have been described above. Examples of this disclosure may be used separately or in various combinations with one or more of the other examples. 
       FIG. 9  is a block diagram illustrating an example of video encoder  20  that may implement the techniques of this disclosure. Video encoder  20  may perform intra- and inter-coding of video blocks within video slices. Intra-coding relies on spatial prediction to reduce or remove spatial redundancy in video within a given video frame or picture. Inter-coding relies on temporal prediction to reduce or remove temporal redundancy in video within adjacent frames or pictures of a video sequence. Intra-mode (I mode) may refer to any of several spatial based coding modes. Inter-modes, such as uni-directional prediction (P mode) or bi-prediction (B mode), may refer to any of several temporal-based coding modes. 
     As shown in  FIG. 9 , video encoder  20  receives a current video block within a video frame to be encoded. In the example of  FIG. 9 , video encoder  20  includes mode select unit  40 , a video data memory  41 , a decoded picture buffer  64 , a summer  50 , a transform processing unit  52 , a quantization unit  54 , and an entropy encoding unit  56 . Mode select unit  40 , in turn, includes a motion compensation unit  44 , a motion estimation unit  42 , an intra prediction processing unit  46 , and a partition unit  48 . For video block reconstruction, video encoder  20  also includes an inverse quantization unit  58 , an inverse transform processing unit  60 , and a summer  62 . A deblocking filter (not shown in  FIG. 9 ) may also be included to filter block boundaries to remove blockiness artifacts from reconstructed video. If desired, the deblocking filter would typically filter the output of summer  62 . Additional filters (e.g., in loop or post loop) may also be used in addition to the deblocking filter. Such filters are not shown for brevity, but if desired, may filter the output of summer  50  (as an in-loop filter). 
     Video data memory  41  may store video data to be encoded by the components of video encoder  20 . The video data stored in video data memory  41  may be obtained, for example, from video source  18 . Decoded picture buffer  64  may be a reference picture memory that stores reference video data for use in encoding video data by video encoder  20 , e.g., in intra- or inter-coding modes. Video data memory  41  and decoded picture buffer  64  may be formed by any of a variety of memory devices, such as dynamic random access memory (DRAM), including synchronous DRAM (SDRAM), magnetoresistive RAM (MRAM), resistive RAM (RRAM), or other types of memory devices. Video data memory  41  and decoded picture buffer  64  may be provided by the same memory device or separate memory devices. In various examples, video data memory  41  may be on-chip with other components of video encoder  20 , or off-chip relative to those components. 
     During the encoding process, video encoder  20  receives a video frame or slice to be coded. The frame or slice may be divided into multiple video blocks. Motion estimation unit  42  and motion compensation unit  44  perform inter-predictive coding of the received video block relative to one or more blocks in one or more reference frames to provide temporal prediction. Intra prediction processing unit  46  may alternatively perform intra-predictive coding of the received video block relative to one or more neighboring blocks in the same frame or slice as the block to be coded to provide spatial prediction. Video encoder  20  may perform multiple coding passes, e.g., to select an appropriate coding mode for each block of video data. 
     Moreover, partition unit  48  may partition blocks of video data into sub-blocks, based on evaluation of previous partitioning schemes in previous coding passes. For example, partition unit  48  may initially partition a frame or slice into LCUs, and partition each of the LCUs into sub-CUs based on rate-distortion analysis (e.g., rate-distortion optimization). Mode select unit  40  may further produce a quadtree data structure indicative of partitioning of an LCU into sub-CUs. Leaf-node CUs of the quadtree may include one or more PUs and one or more TUs. 
     Mode select unit  40  may select one of the coding modes, intra or inter, e.g., based on error results, and provide the resulting intra- or inter-coded block to summer  50  to generate residual block data and to summer  62  to reconstruct the encoded block for use as a reference frame. Mode select unit  40  also provides syntax elements, such as motion vectors, intra-mode indicators, partition information, and other such syntax information, to entropy encoding unit  56 . 
     Motion estimation unit  42  and motion compensation unit  44  may be highly integrated, but are illustrated separately for conceptual purposes. Motion estimation, performed by motion estimation unit  42 , is the process of generating motion vectors, which estimate motion for video blocks. A motion vector, for example, may indicate the displacement of a PU of a video block within a current video frame or picture relative to a predictive block within a reference picture (or other coded unit) relative to the current block being coded within the current picture (or other coded unit). A predictive block is a block that is found to closely match the block to be coded, in terms of pixel difference, which may be determined by sum of absolute difference (SAD), sum of square difference (SSD), or other difference metrics. In some examples, video encoder  20  may calculate values for sub-integer pixel positions of reference pictures stored in decoded picture buffer  64 . For example, video encoder  20  may interpolate values of one-quarter pixel positions, one-eighth pixel positions, or other fractional pixel positions of the reference picture. Therefore, motion estimation unit  42  may perform a motion search relative to the full pixel positions and fractional pixel positions and output a motion vector with fractional pixel precision. 
     Motion estimation unit  42  calculates a motion vector for a PU of a video block in an inter-coded slice by comparing the position of the PU to the position of a predictive block of a reference picture. The reference picture may be selected from a first reference picture list (List 0) or a second reference picture list (List 1), each of which identify one or more reference pictures stored in decoded picture buffer  64 . Motion estimation unit  42  sends the calculated motion vector to entropy encoding unit  56  and motion compensation unit  44 . 
     Motion compensation, performed by motion compensation unit  44 , may involve fetching or generating the predictive block based on the motion vector determined by motion estimation unit  42 . Again, motion estimation unit  42  and motion compensation unit  44  may be functionally integrated, in some examples. Upon receiving the motion vector for the PU of the current video block, motion compensation unit  44  may locate the predictive block to which the motion vector points in one of the reference picture lists. Summer  50  forms a residual video block by subtracting pixel values of the predictive block from the pixel values of the current video block being coded, forming pixel difference values, as discussed below. In general, motion estimation unit  42  performs motion estimation relative to luma components, and motion compensation unit  44  uses motion vectors calculated based on the luma components for both chroma components and luma components. Mode select unit  40  may also generate syntax elements associated with the video blocks and the video slice for use by video decoder  30  in decoding the video blocks of the video slice. 
     Intra prediction processing unit  46  may intra-predict a current block, as an alternative to the inter-prediction performed by motion estimation unit  42  and motion compensation unit  44 , as described above. In particular, intra prediction processing unit  46  may determine an intra-prediction mode to use to encode a current block. In some examples, intra prediction processing unit  46  may encode a current block using various intra-prediction modes, e.g., during separate encoding passes, and intra prediction processing unit  46  (or mode select unit  40 , in some examples) may select an appropriate intra-prediction mode to use from the tested modes. 
     For example, intra prediction processing unit  46  may calculate rate-distortion values using a rate-distortion analysis for the various tested intra-prediction modes, and select the intra-prediction mode having the best rate-distortion characteristics among the tested modes. Rate-distortion analysis generally determines an amount of distortion (or error) between an encoded block and an original, unencoded block that was encoded to produce the encoded block, as well as a bit rate (that is, a number of bits) used to produce the encoded block. Intra prediction processing unit  46  may calculate ratios from the distortions and rates for the various encoded blocks to determine which intra-prediction mode exhibits the best rate-distortion value for the block. 
     After selecting an intra-prediction mode for a block, intra prediction processing unit  46  may provide information indicative of the selected intra-prediction mode for the block to entropy encoding unit  56 . Entropy encoding unit  56  may encode the information indicating the selected intra-prediction mode. Video encoder  20  may include in the transmitted bitstream configuration data, which may include a plurality of intra-prediction mode index tables and a plurality of modified intra-prediction mode index tables (also referred to as codeword mapping tables), definitions of encoding contexts for various blocks, and indications of a most probable intra-prediction mode, an intra-prediction mode index table, and a modified intra-prediction mode index table to use for each of the contexts. 
     Video encoder  20  forms a residual video block by subtracting the prediction data from mode select unit  40  from the original video block being coded. Summer  50  represents the component or components that perform this subtraction operation. Transform processing unit  52  applies a transform, such as a discrete cosine transform (DCT) or a conceptually similar transform, to the residual block, producing a video block comprising residual transform coefficient values. Transform processing unit  52  may perform other transforms which are conceptually similar to DCT. Wavelet transforms, integer transforms, sub-band transforms or other types of transforms could also be used. In any case, transform processing unit  52  applies the transform to the residual block, producing a block of residual transform coefficients. The transform may convert the residual information from a pixel value domain to a transform domain, such as a frequency domain. Transform processing unit  52  may send the resulting transform coefficients to quantization unit  54 . 
     Quantization unit  54  quantizes the transform coefficients to further reduce bit rate. The quantization process may reduce the bit depth associated with some or all of the coefficients. The degree of quantization may be modified by adjusting a quantization parameter. In some examples, quantization unit  54  may then perform a scan of the matrix including the quantized transform coefficients. Alternatively, entropy encoding unit  56  may perform the scan. 
     Following quantization, entropy encoding unit  56  entropy codes the quantized transform coefficients. For example, entropy encoding unit  56  may perform context adaptive variable length coding (CAVLC), context adaptive binary arithmetic coding (CABAC), syntax-based context-adaptive binary arithmetic coding (SBAC), probability interval partitioning entropy (PIPE) coding or another entropy coding technique. In the case of context-based entropy coding, context may be based on neighboring blocks. Following the entropy coding by entropy encoding unit  56 , the encoded bitstream may be transmitted to another device (e.g., video decoder  30 ) or archived for later transmission or retrieval. 
     Inverse quantization unit  58  and inverse transform processing unit  60  apply inverse quantization and inverse transformation, respectively, to reconstruct the residual block in the pixel domain, e.g., for later use as a reference block. Motion compensation unit  44  may calculate a reference block by adding the residual block to a predictive block of one of the frames of decoded picture buffer  64 . Motion compensation unit  44  may also apply one or more interpolation filters to the reconstructed residual block to calculate sub-integer pixel values for use in motion estimation. Summer  62  adds the reconstructed residual block to the motion compensated prediction block produced by motion compensation unit  44  to produce a reconstructed video block for storage in decoded picture buffer  64 . The reconstructed video block may be used by motion estimation unit  42  and motion compensation unit  44  as a reference block to inter-code a block in a subsequent video frame. 
     Video encoder  20  may implement various techniques of this disclosure to derive quantization parameter (QP) values for a currently-encoded block from the block&#39;s spatio-temporal neighboring blocks, and/or to apply scaling operations to all (e.g., DC and AC) transform coefficients of the currently-encoded block. 
     Reference is also made to  FIG. 8  in the description below. In some implementations, video encoder  20  may derive a reference QP value for currently-coded block  152  from attached blocks (CUs) of the spatio-temporal neighborhood. That is, video encoder  20  may derive the QP value for currently-coded block  152  using top neighbor block  158  and left neighbor block  156 . An example of such an implementation in which video encoder  20  derives the QP value for currently-coded block  152  using top neighbor block  158  and left neighbor block  156  is described by the pseudocode below: 
     
       
         
           
               
               
             
               
                   
                   
               
             
            
               
                   
                 Char TComDataCU::getRefQP( UInt uiCurrAbsIdxInCtu ) 
               
               
                   
                 { 
               
               
                   
                    TComDataCU* cULeft = getQpMinCuLeft ( lPartIdx, 
               
               
                   
                 m_absZIdxInCtu + uiCurrAbsIdxInCtu ); 
               
               
                   
                    TComDataCU* cUAbove = getQpMinCuAbove( aPartIdx, 
               
               
                   
                 m_absZIdxInCtu + uiCurrAbsIdxInCtu ); 
               
               
                   
                    return (((cULeft? cULeft-&gt;getQP( lPartIdx ): 
               
               
                   
                 m_QuLastCodedQP) + (cUAbove? cUAbove-&gt;getQP( aPartIdx ): 
               
               
                   
                 m_QuLastCodedQP) + 1) &gt;&gt; 1); 
               
               
                   
                 } 
               
               
                   
                   
               
            
           
         
       
     
     In some implementations, video encoder  20  may derive the QP value for currently-coded block  152  by taking into consideration one or more QP values of reference samples. An example of such an implementation, in which video encoder  20  uses the QP value(s) of the reference samples to derive the QP value for currently-coded block  152  is described by the pseudocode below: 
     
       
         
           
               
               
             
               
                   
                   
               
             
            
               
                   
                 Char TComDataCU::getRefQP2( UInt uiCurrAbsIdxInCtu ) 
               
               
                   
                 { 
               
               
                   
                    TComDataCU* cULeft = getQpMinCuLeft ( lPartIdx, 
               
               
                   
                 m_absZIdxInCtu + uiCurrAbsIdxInCtu ); 
               
               
                   
                    TComDataCU* cUAbove = getQpMinCuAbove( aPartIdx, 
               
               
                   
                 m_absZIdxInCtu + uiCurrAbsIdxInCtu ); 
               
               
                   
                    TComDataCU* cURefer = getQpMinCuReference( aPartIdx, 
               
               
                   
                 m_absZIdxInCtu + uiCurrAbsIdxInCtu ); 
               
               
                   
                    return value = function (cULeft-&gt;getLastQP( ), 
               
               
                   
                 cUAbove-&gt;getLastQP( ), cURefer -&gt;getLastQP( )); 
               
               
                   
                 } 
               
               
                   
                   
               
            
           
         
       
     
     According to some implementations of the techniques described herein, video encoder  20  may store QPs that are applied to samples of reference block(s) and/or global QPs (e.g., slice-level QPs) for all pictures utilized as reference pictures. According to some implementation of the techniques described herein, video encoder  20  may store the scaling parameters applied to samples of reference block(s) and/or global scaling parameters (e.g., slice-level scaling) for all pictures utilized as reference pictures. If a block of reference samples overlaps with multiple CUs of the block partitioning (thus possibly having different QPs across the partitions), video encoder  20  may derive the QP from a multitude of the available QPs. For example, video encoder  20  may derive the QP for currently-coded block  152  by implementing a process of averaging on the multiple available QPs. An example of an implementation according to which video encoder  20  may derive the QP value for currently-coded block  152  by averaging multiple available QPs from reference samples is described by the pseudocode below: 
     
       
         
           
               
               
             
               
                   
                   
               
             
            
               
                   
                 Int sum= 0; 
               
               
                   
                  for (Int i=0; i &lt; numMinPart; i++) 
               
               
                   
                  { 
               
               
                   
                     sum += 
               
               
                   
                     m_phInferQP[COMPONENT_Y][uiAbsPartIdxInCTU + i]; 
               
               
                   
                  } 
               
               
                   
                  avgQP = (sum)/numMinPart; 
               
               
                   
                   
               
            
           
         
       
     
     In yet another implementation of the QP-derivation techniques described herein, video encoder  20  may derive the QP as a function of the average brightness of luma components, such as from a lookup table (LUT). This implementation is described by the following pseudocode, where avgPred′ is an average brightness of the reference samples: 
       QP=PQ_LUT[avgPred]; 
     According to some implementations of the QP-derivation techniques described herein, video encoder  20  may derive a reference QP value from one or more global QP values. An example of a global QP value is a QP value that is specified at the slice level. This implementation is described by the following pseudocode: 
       qp=(((Int)pcCU−&gt;getSlice( )&gt;getSliceQp( )+ iD Qp+52+2*qp Bd Offset Y )%(52+qp Bd Offset Y ))−qp Bd Offset Y;  
 
     According to some implementations of the QP-derivation techniques described herein, video encoder  20  may derive QP values by utilizing one or more reference sample values. This implementation is described by the following pseudocode: 
       QP=PQ_LUT[avgPred]; 
     In the pseudocode above, “PQ_LUT” represents a look up table which video encoder  20  may utilize to map an average brightness of the predicted block (“avgPred”) value to an associated PQ value. Video encoder  20  may compute the value of avgPred as function of reference samples, such as by computing an average value of the reference samples. Examples of average values that video encoder  20  may use in accordance with the calculations of this disclosure include one or more of mean, median, and mode values. 
     In some implementations, video encoder  20  may derive scaling parameters instead of QP values. In other implementations, video encoder  20  may use a conversion process that converts derived QP value(s) to scale parameter(s), or vice versa. In some implementations, video encoder  20  may utilize an analytical expression to derive a QP value from one or more reference samples. For instance, to utilize an analytical expression, video encoder  20  may use a parametric derivation model. 
       FIG. 10  is a block diagram illustrating an example of video decoder  30  that may implement the techniques of this disclosure. In the example of  FIG. 10 , video decoder  30  includes an entropy decoding unit  70 , a video data memory  71 , motion compensation unit  72 , intra prediction processing unit  74 , inverse quantization unit  76 , inverse transform processing unit  78 , decoded picture buffer  82  and summer  80 . Video decoder  30  may, in some examples, perform a decoding pass generally reciprocal to the encoding pass described with respect to video encoder  20  ( FIG. 9 ). Motion compensation unit  72  may generate prediction data based on motion vectors received from entropy decoding unit  70 , while intra prediction processing unit  74  may generate prediction data based on intra-prediction mode indicators received from entropy decoding unit  70 . 
     Video data memory  71  may store video data, such as an encoded video bitstream, to be decoded by the components of video decoder  30 . The video data stored in video data memory  71  may be obtained, for example, from computer-readable medium  16 , e.g., from a local video source, such as a camera, via wired or wireless network communication of video data, or by accessing physical data storage media. Video data memory  71  may form a coded picture buffer (CPB) that stores encoded video data from an encoded video bitstream. Decoded picture buffer  82  may be a reference picture memory that stores reference video data for use in decoding video data by video decoder  30 , e.g., in intra- or inter-coding modes. Video data memory  71  and decoded picture buffer  82  may be formed by any of a variety of memory devices, such as dynamic random access memory (DRAM), including synchronous DRAM (SDRAM), magnetoresistive RAM (MRAM), resistive RAM (RRAM), or other types of memory devices. Video data memory  71  and decoded picture buffer  82  may be provided by the same memory device or separate memory devices. In various examples, video data memory  71  may be on-chip with other components of video decoder  30 , or off-chip relative to those components. 
     During the decoding process, video decoder  30  receives an encoded video bitstream that represents video blocks of an encoded video slice and associated syntax elements from video encoder  20 . Entropy decoding unit  70  of video decoder  30  entropy decodes the bitstream to generate quantized coefficients, motion vectors or intra-prediction mode indicators, and other syntax elements. Entropy decoding unit  70  forwards the motion vectors to and other syntax elements to motion compensation unit  72 . Video decoder  30  may receive the syntax elements at the video slice level and/or the video block level. 
     When the video slice is coded as an intra-coded (I) slice, intra prediction processing unit  74  may generate prediction data for a video block of the current video slice based on a signaled intra prediction mode and data from previously decoded blocks of the current frame or picture. When the video frame is coded as an inter-coded (i.e., B or P) slice, motion compensation unit  72  produces predictive blocks for a video block of the current video slice based on the motion vectors and other syntax elements received from entropy decoding unit  70 . The predictive blocks may be produced from one of the reference pictures within one of the reference picture lists. Video decoder  30  may construct the reference picture lists, List 0 and List 1, using default construction techniques based on reference pictures stored in decoded picture buffer  82 . Motion compensation unit  72  determines prediction information for a video block of the current video slice by parsing the motion vectors and other syntax elements, and uses the prediction information to produce the predictive blocks for the current video block being decoded. For example, motion compensation unit  72  uses some of the received syntax elements to determine a prediction mode (e.g., intra- or inter-prediction) used to code the video blocks of the video slice, an inter-prediction slice type (e.g., B slice or P slice), construction information for one or more of the reference picture lists for the slice, motion vectors for each inter-encoded video block of the slice, inter-prediction status for each inter-coded video block of the slice, and other information to decode the video blocks in the current video slice. 
     Motion compensation unit  72  may also perform interpolation based on interpolation filters. Motion compensation unit  72  may use interpolation filters as used by video encoder  20  during encoding of the video blocks to calculate interpolated values for sub-integer pixels of reference blocks. In this case, motion compensation unit  72  may determine the interpolation filters used by video encoder  20  from the received syntax elements and use the interpolation filters to produce predictive blocks. 
     Inverse quantization unit  76  inverse quantizes, i.e., de-quantizes, the quantized transform coefficients provided in the bitstream and decoded by entropy decoding unit  70 . The inverse quantization process may include use of a quantization parameter QP Y  calculated by video decoder  30  for each video block in the video slice to determine a degree of quantization and, likewise, a degree of inverse quantization that should be applied. Inverse transform processing unit  78  applies an inverse transform, e.g., an inverse DCT, an inverse integer transform, or a conceptually similar inverse transform process, to the transform coefficients in order to produce residual blocks in the pixel domain. 
     After motion compensation unit  72  generates the predictive block for the current video block based on the motion vectors and other syntax elements, video decoder  30  forms a decoded video block by summing the residual blocks from inverse transform processing unit  78  with the corresponding predictive blocks generated by motion compensation unit  72 . Summer  80  represents the component or components that perform this summation operation. If desired, a deblocking filter may also be applied to filter the decoded blocks in order to remove blockiness artifacts. Other loop filters (either in the coding loop or after the coding loop) may also be used to smooth pixel transitions, or otherwise improve the video quality. The decoded video blocks in a given frame or picture are then stored in decoded picture buffer  82 , which stores reference pictures used for subsequent motion compensation. Decoded picture buffer  82  also stores decoded video for later presentation on a display device, such as display device  32  of  FIG. 1 . 
     Video decoder  30  may receive, in an encoded video bitstream, a delta QP value that is derived from the QP value obtained by video encoder  20  according to one or more of the techniques described above. Using the delta QP value, video decoder  30  may obtain the QP value pertaining to a block that is currently being decoded, such as currently-coded block  152  illustrated in  FIG. 8 . In turn, video decoder  30  may dequantize currently-coded block  152  using the QP value. 
     In instances where video decoder  30  receives scaling parameters for currently-coded block  152 , video decoder  30  may use the scaling parameters to implement an inverse scaling process that is generally reciprocal to various that uses the scaled values DC′ and AC′ as operands. That is, video decoder  30  may apply the scaling parameters to inverse-scale the scaled DC transform coefficients DC′ and the scaled AC transform coefficients AC′ to obtain inverse-scaled DC coefficients DC″ and inverse-scaled AC transform coefficients AC″ as expressed by the equations below. Video decoder  30  may implement the inverse scaling operations as illustrated in the following equations: 
       DC″=DC′/scale(fun1(DC′,avgPred)); and
 
       AC″=AC′/scale(fun2(DC″,avgPred))
 
     The terms ‘fun 1 ’ and ‘fun 2 ’ define scale derivation functions/processes that use, as arguments, an average of reference samples and DC-based values. As illustrated with respect to the inverse-scaling techniques implemented by video decoder  30 , the techniques of this disclosure enable the use of DC transform coefficient values in the derivation of both the DC and AC transform coefficient values. In this way, techniques of this disclosure enable video decoder  30  to leverage DC transform coefficient values in inverse-scaling operations, regardless of whether the inverse-scaling operations are performed in place of, or in combination with, quantization and dequantization of transform coefficients. 
       FIG. 11  is a flowchart illustrating an example process  170  that video decoder  30  may perform, according to various aspects of this disclosure. Process  170  may begin when video decoder  30  receives an encoded video bitstream that includes an encoded representation of current block  152  ( 172 ). Video decoder  30  may reconstruct a QP value that is based on the spatio-temporal neighboring QP information for current block  152  ( 174 ). For instance, video decoder  30  may reconstruct the QP from a delta QP value signaled in the encoded video bitstream. The reconstructed QP value may be based on QP information from one or more of blocks  154 - 158  illustrated in  FIG. 8 . As discussed above, to reconstruct the QP value, video decoder  30  may average QP values of two or more of the spatio-temporal neighboring blocks  154 - 158  to produce a reference QP value, then add the delta QP value to the reference QP value to ultimately generate the reconstructed QP value for the current block. In turn, video decoder  30  (and more particularly, inverse quantization unit  76 ) may dequantize (i.e., inverse-quantize) CABAC-decoded transform coefficients of current block  152  using the reconstructed QP value that is based on the spatio-temporal neighboring QP information ( 176 ). In some examples, video decoder  30  may obtain a reference QP value for samples of current block  152  based on samples of the spatio-temporal neighborhood, and may add the delta QP value to the reference QP value to derive the QP value for dequantizing the samples of current block  152 . 
       FIG. 12  is a flowchart illustrating an example process  190  that video decoder  30  may perform, according to various aspects of this disclosure. Process  190  may begin when video decoder  30  receives an encoded video bitstream that includes an encoded representation of current block  152  ( 192 ). Video decoder  30  may reconstruct a scaling parameter that is based on the spatio-temporal neighboring scaling information for current block  152  ( 194 ). For instance, the reconstructed scaling parameter may be based on scaling information from one or more of blocks  154 - 158  illustrated in  FIG. 8 . In turn, video decoder  30  may inverse scale current block  152  using the reconstructed scaling parameter that is based on the spatio-temporal neighboring QP information ( 196 ). In some examples, video decoder  30  may apply a first inverse scaling derivation process to a plurality of DC transform coefficients of the transform coefficients of current block  152  to obtain a plurality of inverse-scaled DC transform coefficients, and may apply a second inverse scaling derivation process to the plurality of inverse-scaled DC transform coefficients of the transform coefficients of current block  152  to obtain a plurality of inverse-scaled AC transform coefficients. 
       FIG. 13  is a flowchart illustrating an example process  210  that video encoder  20  may perform, according to various aspects of this disclosure. Process  210  may begin when video encoder  20  derives a QP value for current block  152  from spatio-temporal neighboring QP information of current block  152  ( 212 ). Video encoder  20  may quantize current block  152  using the QP value derived from the spatio-temporal neighboring QP information ( 214 ). In turn, video encoder  20  may signal a delta QP value that derived from the QP that is based on the spatio-temporal neighboring QP information in an encoded video bitstream ( 216 ). In some examples, video encoder  20  may select neighbor QP values associated with samples of two or more of the spatial neighbor blocks  154  and/or  156  and/or temporal neighbor block  158 . In some examples, video encoder  20  may average the selected neighbor QP values to obtain an average QP value, and may derive the QP value for the current block from the average QP value. In some examples, video encoder  20  may obtain a reference QP value for samples of current block  152  based on samples of the spatio-temporal neighborhood. In these examples, video encoder  20  may subtract the reference QP value from the QP value to derive a delta quantization parameter (QP) value for the samples of current block  152 , and may signal the delta QP value in an encoded video bitstream. 
       FIG. 14  is a flowchart illustrating an example process  240  that video encoder  20  may perform, according to various aspects of this disclosure. Process  240  may begin when video encoder  20  derives a scaling parameter for current block  152  from spatio-temporal neighboring scaling information of current block  152  ( 242 ). Video encoder  20  may scale current block  152  using the scaling parameter derived from the spatio-temporal neighboring scaling information ( 244 ). In turn, video encoder  20  may signal the scaling parameter that is based on the spatio-temporal neighboring scaling information in an encoded video bitstream ( 246 ). 
     As described above, the disclosed systems and techniques also incorporate or include several algorithms for derivation of quantization or scaling parameters from a spatio-temporal neighborhood of the signal. That is, example systems and techniques of this disclosure are directed to obtaining one or more parameter values that are used to modify residual data associated with the current block in a coding process. As used herein, a parameter value that is used to modify residual data may include a quantization parameter (used to modify the residual data by quantizing or dequantizing residual data in an encoding process or decoding process, respectively), or a scaling parameter (used to modify the residual data by scaling or inverse-scaling residual data in an encoding process or decoding process, respectively). 
     Certain aspects of this disclosure have been described with respect to extensions of the HEVC standard for purposes of illustration. However, the techniques described in this disclosure may be useful for other video coding processes, including other standard or proprietary video coding processes not yet developed. 
     A video coder, as described in this disclosure, may refer to a video encoder or a video decoder. Similarly, a video coding unit may refer to a video encoder or a video decoder. Likewise, video coding may refer to video encoding or video decoding, as applicable. 
     It is to be recognized that depending on the example, certain acts or events of any of the techniques described herein can be performed in a different sequence, may be added, merged, or left out altogether (e.g., not all described acts or events are necessary for the practice of the techniques). Moreover, in certain examples, acts or events may be performed concurrently, e.g., through multi-threaded processing, interrupt processing, or multiple processors, rather than sequentially. 
     In one or more examples, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium and executed by a hardware-based processing unit. Computer-readable media may include computer-readable storage media, which corresponds to a tangible medium such as data storage media, or communication media including any medium that facilitates transfer of a computer program from one place to another, e.g., according to a communication protocol. In this manner, computer-readable media generally may correspond to (1) tangible computer-readable storage media which is non-transitory or (2) a communication medium such as a signal or carrier wave. Data storage media may be any available media that can be accessed by one or more computers or one or more processors to retrieve instructions, code and/or data structures for implementation of the techniques described in this disclosure. A computer program product may include a computer-readable medium. 
     By way of example, and not limitation, such computer-readable storage media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage, or other magnetic storage devices, flash memory, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer. Also, any connection is properly termed a computer-readable medium. For example, if instructions are transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. It should be understood, however, that computer-readable storage media and data storage media do not include connections, carrier waves, signals, or other transitory media, but are instead directed to non-transitory, tangible storage media. Disk and disc, as used herein, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc, where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media. 
     Instructions may be executed by one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors, application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Accordingly, the term “processor,” as used herein may refer to any of the foregoing structure or any other structure suitable for implementation of the techniques described herein. In addition, in some aspects, the functionality described herein may be provided within dedicated hardware and/or software modules configured for encoding and decoding, or incorporated in a combined codec. Also, the techniques could be fully implemented in one or more circuits or logic elements. 
     The techniques of this disclosure may be implemented in a wide variety of devices or apparatuses, including a wireless handset, an integrated circuit (IC) or a set of ICs (e.g., a chip set). Various components, modules, or units are described in this disclosure to emphasize functional aspects of devices configured to perform the disclosed techniques, but do not necessarily require realization by different hardware units. Rather, as described above, various units may be combined in a codec hardware unit or provided by a collection of interoperative hardware units, including one or more processors as described above, in conjunction with suitable software and/or firmware. 
     Various examples have been described. These and other examples are within the scope of the following claims.