Patent Publication Number: US-9838690-B1

Title: Selective prediction signal filtering

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of U.S. patent application Ser. No. 13/546,402, which was filed on Jul. 11, 2012. 
    
    
     TECHNICAL FIELD 
     The present invention relates in general to video encoding and decoding. 
     BACKGROUND 
     An increasing number of applications today make use of digital video for various purposes including, for example, remote business meetings via video conferencing, high definition video entertainment, video advertisements, and sharing of user-generated videos. As technology is evolving, users have higher expectations for video quality and expect high resolution video even when transmitted over communications channels having limited bandwidth. 
     SUMMARY 
     Disclosed herein are implementations of systems, methods, and apparatuses for selective prediction signal filtering. 
     An aspect of the disclosed implementations is a method for encoding a video signal having a frame. The method includes determining a first performance measurement for a first set of prediction samples identified for a group of pixels of the frame using a first prediction mode, generating a filtered set of prediction samples for the group of pixels by applying a filter to a second set of prediction samples, wherein at least one of the filtered set of prediction samples or the second set of prediction samples are identified using a second prediction mode, determining a second performance measurement for the filtered set of prediction samples, generating, using a processor, a residual based on the filtered set of prediction samples and the group of pixels if the second performance measurement exceeds the first performance measurement, and encoding the frame using the residual. 
     An aspect of the disclosed implementations is an apparatus for encoding a video signal having a frame. The apparatus includes a memory and a processor configured to execute instructions stored in the at least one memory to: determine a first performance measurement for a first set of prediction samples identified for a group of pixels of the frame using a first prediction mode, generate a filtered set of prediction samples for the group of pixels by applying a filter to a second set of prediction samples, wherein at least one of the filtered set of prediction samples or the second set of prediction samples are identified using a second prediction mode, determine a second performance measurement for the filtered set of prediction samples, generate a residual based on the filtered set of prediction samples and the group of pixels if the second performance measurement exceeds the first performance measurement, and encode the frame using the residual. 
     An aspect of the disclosed implementations is a method for decoding an encoded video signal. The method includes decoding a prediction mode, a filter indicator, and a residual associated with a group of pixels of a frame of the encoded video signal, identifying a set of prediction samples for decoding the group of pixels based on the prediction mode, applying a filter to the identified set of prediction samples based on the filter indicator to generate a filtered set of prediction samples, and generating a reconstructed group of pixels using the filtered set of prediction samples and the residual. 
     These and other implementations will be described in additional detail hereafter. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The description herein makes reference to the accompanying drawings wherein like reference numerals refer to like parts throughout the several views, and wherein: 
         FIG. 1A  is a schematic of a video encoding and decoding system; 
         FIG. 1B  is a block diagram of an example internal configuration of the transmitting station and the receiving station of  FIG. 1A ; 
         FIG. 2  is a diagram of a typical video stream to be encoded and/or decoded; 
         FIG. 3  is a block diagram of an encoding technique in accordance with an implementation of this disclosure; 
         FIG. 4  is a block diagram of a decoding technique in accordance with an implementation of this disclosure; 
         FIG. 5  is a flow chart of a technique for performance measurement in accordance with an implementation of this disclosure; 
         FIG. 6A  is a schematic diagram of a set of pixels, a filter dependent region of pixels using one type of filter, and a target pixel in accordance with an implementation of this disclosure; 
         FIG. 6B  is a schematic diagram of filtering a target pixel using one type of filter in accordance with an implementation of this disclosure; 
         FIG. 6C  is a schematic diagram of a set of pixels, a filter dependent region of pixels using another type of filter, and a target pixel in accordance with an implementation of this disclosure; 
         FIG. 6D  is a schematic diagram of filtering a target pixel using another type of filter in accordance with an implementation of this disclosure; 
         FIG. 7  is a flow chart of a technique for applying a filter to a set of pixels in accordance with an implementation of this disclosure; 
         FIG. 8  is a flow chart of a technique for selective prediction signal processing in accordance with an implementation of this disclosure; 
         FIG. 9  is a flow chart of a technique for decoding a compressed bitstream encoded using selective prediction signal processing in accordance with an implementation of this disclosure. 
     
    
    
     DETAILED DESCRIPTION 
     To permit transmission of digital video streams while limiting bandwidth consumption, video encoding and decoding implementations can incorporate various compression schemes. These compression schemes generally break the image up into blocks and use one or more techniques to limit the amount of information included in a resulting compressed video bitstream for transmission. The bitstream, once received, is then decoded to re-create the blocks and the source images from the limited information. Digital video can be encoded into video bitstreams using formats such as VPx, H.264, MPEG, MJPEG, and/or others. 
     Encoding a video stream, or a portion thereof, such as a frame or a block, can include using temporal and spatial similarities in the video stream to improve coding efficiency. For example, a current block of a video stream may be encoded based on a previously encoded block in the video stream by predicting motion and color information for the current block based on the previously encoded block and identifying a difference (residual) between the predicted values and the current block. Inter prediction can include using a previously encoded block from a previously encoded frame (reference frame). Intra prediction can include using a previously encoded block from the current frame. Using the previously encoded block can include using less than all of the pixels of the previously encoded block to generate a prediction block. Intra prediction can be used for encoding, for example, a frame of video or individual images. 
     The type of prediction utilized for a block or frame can be identified by a prediction mode which can be encoded into the compressed video bitstream to enable decoding. For example, intra prediction can include predicting values for a current block based on values of spatially proximate previously encoded blocks in the current frame which can be identified using one or more intra prediction modes, such as horizontal prediction (H_PRED), vertical prediction (V_PRED), DC prediction (DC_PRED), or TrueMotion prediction (TM_PRED). For example, inter prediction can include predicting values of a current block based on values of a reference block from a previously decoded frame or a reference frame that can be identified by a motion vector using one or more inter prediction modes, such as the use of neighboring motion vectors (MV_NEAR or MV_NEAREST), differentially encoded motion vectors (NEWMV), sub-block motion vectors (SPLITMV), and reference frame identifier (e.g., last frame, golden frame, alternate reference frame). 
     Many prediction techniques use block based prediction and quantized block transforms. The use of block based prediction and quantized block transforms can give rise to picture quality degradation, visual artifacts and discontinuities along block boundaries during encoding. These degradations, artifacts, and discontinuities can be visually disturbing and can reduce the quality of the decoded video and the effectiveness of the reference frame used as a predictor for subsequent frames. These degradations, artifacts, and discontinuities can be reduced by the application of selective prediction signal filtering, performance measurement for loop filtering, or both. 
     Selective prediction signal filtering can include generating a performance measurement for an encoding of a group of pixels using various prediction mode and filter combinations. The group of pixels can be, for example, a segment, macroblock, subblock, block, or individual pixel of a frame. Performance measurements can include, for example, a rate distortion measurement, sum of squared differences measurement, or any available error metric, rate metric, or combination thereof. Performance measurements can be made for a prediction mode with filtering and without filtering. In an implementation, a prediction mode can be defined to include filtering or not include filtering. Filtering can include applying a Finite Impulse Response (FIR) filter in the horizontal and vertical directions to pixels in the group of pixels. In an implementation, filtering can include the use of other filters or filters applied in other directions. In an implementation, some pixels of the group of pixels may not be filtered based on pixel values to be used for filtering and threshold values defined for use with the filter being used. Performance measurements can be made for a single filter per prediction mode or multiple potential filters (e.g., filter type and/or filter strength) per prediction mode. 
     A prediction mode and filter can be selected for encoding the group of pixels based on the performance measurement, by, for example, selecting a prediction mode and filter having a smallest rate distortion (selecting a filter can include not applying a filter). The selected prediction mode and filter can be used to identify prediction samples used to generate a residual of the group of pixels for encoding. The encoding can include data indicative of the selected prediction mode and filter. A decoder can decode the encoding by, for example, identifying prediction samples for decoding using the selected prediction mode and by using the selected filter (or absence thereof). 
     Performance measurement for loop filtering can include generating performance measurements for a reconstruction of a group of pixels using various filter type and strength combinations. For example, available filter type and strengths can be applied to the group of pixels and a rate distortion measurement can be generated for each application. The resulting rate distortion measurements can be compared, and a filter type and strength having a lowest rate distortion measurement can be selected. The selected filter type and strength can be used to filter pixels in the reconstruction of the group of pixels. The selected filter type and strength can be included in the encoding of the group of pixels so that a decoder, when decoding the encoding, can apply the selected filter type and strength to the reconstruction of the group of pixels generated by the decoder. 
       FIG. 1A  is a schematic of a video encoding and decoding system  10 . An exemplary transmitting station  12  can be, for example, a computer having an internal configuration of hardware such as that described in  FIG. 1B . However, other suitable implementations of the transmitting station  12  are possible. For example, the processing of the transmitting station  12  can be distributed among multiple devices. 
     A network  14  connects the transmitting station  12  and a receiving station  16 . Specifically, a video stream can be encoded in the transmitting station  12  and the encoded video stream can be decoded in the receiving station  16 . The network  14  can, for example, be the Internet. The network  14  can also be a local area network (LAN), wide area network (WAN), virtual private network (VPN), or any other means of transferring the video stream from the transmitting station  12 . 
     The receiving station  16 , in one example, can be a computer having an internal configuration of hardware such as that described in  FIG. 1B . Other suitable implementations of the receiving station  16  are possible. For example, the processing of the receiving station  16  can be distributed among multiple devices. 
     Other implementations of the encoder and decoder system  10  are possible. In an implementation, additional components can be added to the encoder and decoder system  10 . For example, a second receiving station can be added. In an implementation, components can be removed from the encoder and decoder system  10 . For example, the receiving station  16  and/or network  14  can be omitted, and the techniques and processes described herein (or a subset thereof) can be implemented using station  12 . 
       FIG. 1B  is a block diagram of an example internal configuration of transmitting station  12  and receiving station  16  of  FIG. 1A . Each of stations  12 ,  16  can be in the form of a computing system including multiple computing devices, or in the form of a single computing device, for example, a mobile phone, a tablet computer, a laptop computer, a notebook computer, a desktop computer, and the like. 
     The CPU  24  in stations  12 ,  16  can be a conventional central processing unit. Alternatively, the CPU  24  can be any other type of device, or multiple devices, capable of manipulating or processing information now-existing or hereafter developed. Although the disclosed embodiments can be practiced with a single processor as shown, e.g. CPU  24 , advantages in speed and efficiency can be achieved using more than one processor. 
     The memory  26  in stations  12 ,  16  can be a random access memory device (RAM). Any other suitable type of storage device can be used as the memory  26 . The memory  26  can include code and data  27  that is accessed by the CPU  24  using a bus  30 . The memory  26  can further include an operating system  32  and application programs  34 , the application programs  34  including programs that permit the CPU  24  to perform the methods described here. For example, the application programs  34  can include applications  1  through N which further include a video communication application that can perform the methods described here. Stations  12 ,  16  can also include a secondary storage  36 , which can, for example, be a memory card used with a mobile computing device. Because video communication can contain a significant amount of information, they can be stored in whole or in part in the secondary storage  36  and loaded into the memory  26  as needed for processing. 
     Stations  12 ,  16  can also include one or more output devices, such as display  28 , which can be a touch sensitive display that combines a display with a touch sensitive element that is operable to sense touch inputs. The display  28  can be coupled to the CPU  24  via the bus  30 . Other output devices that permit a user to program or otherwise use stations  12 ,  16  can be provided in addition to or as an alternative to the display  28 . When the output device is or includes a display, the display can be implemented in various ways, including by a liquid crystal display (LCD) or a cathode-ray tube (CRT) or light emitting diode (LED) display, such as an OLED display. 
     Stations  12 ,  16  can also include or be in communication with an image-sensing device  38 , for example a camera, or any other image-sensing device  38  now existing or hereafter developed. The image-sensing device  38  can be configured to receive images, for example, of the face of a device user while the device user is operating one of stations  12 ,  16 . 
     Although  FIG. 1B  depicts the CPU  24  and the memory  26  of stations  12 , 16  as being integrated into a single unit, other configurations can be utilized. The operations of the CPU  24  can be distributed across multiple machines (each machine having one or more of processors) which can be coupled directly or across a local area or other network. The memory  26  can be distributed across multiple machines such as network-based memory or memory in multiple machines performing the operations of stations  12 ,  16 . Although depicted here as a single bus, the bus  30  of stations  12 ,  16  can be composed of multiple buses. Further, the secondary storage  36  can be directly coupled to the other components of stations  12 ,  16  or can be accessed via a network and can comprise a single integrated unit such as a memory card or multiple units such as multiple memory cards. Stations  12 ,  16  can thus be implemented in a wide variety of configurations. 
       FIG. 2  is a diagram of a typical video stream  200  to be encoded and/or decoded. Video coding formats, such as VPx or H.264, provide a defined hierarchy of layers for a video stream. The video stream  200  includes a video sequence  202 . At the next level, the video sequence  202  includes a number of adjacent frames  204 . While three frames are depicted in adjacent frames  204 , the video sequence  202  can include any number of adjacent frames. The adjacent frames  204  can then be further subdivided into a single frame  206 . At the next level, the single frame  206  can be divided into a series of blocks  208 , which can contain data corresponding to, for example, a 16×16 pixel group of displayed pixels in the frame  206 . Each block can contain luminance and chrominance data for the corresponding pixels. The blocks  208  can also be of any other suitable size such as 16×8 pixel groups or 8×16 pixel groups. The terms block and macroblock can be used interchangeably herein. 
       FIG. 3  is a block diagram of an encoder  300  in accordance with an implementation of this disclosure. Encoder  300  can be implemented, for example, in transmitting station  12  by providing a computer software program stored in memory  26  or storage  36 . The computer software program can include machine instructions that, when executed by CPU  24 , cause transmitting station  12  to encode video data in the manner described in  FIG. 3 . Encoder  300  can also be implemented as hardware (e.g., an ASIC or FPGA) included in a computing device. 
     Encoder  300  encodes an input video stream  302  (e.g., video stream  200 ). Encoder  300  has the following stages to perform the various functions in a forward path (shown by the solid connection lines) to produce an encoded or a compressed bitstream  320 : an intra/inter prediction stage  304 , a transform stage  306 , a quantization stage  308 , and an entropy encoding stage  310 . Encoder  300  also includes a reconstruction path (shown by the dotted connection lines) to reconstruct a frame for encoding of further blocks. Encoder  300  can include the following stages to perform the various functions in the reconstruction path: a dequantization stage  312 , an inverse transform stage  314 , a reconstruction stage  316 , and a loop filtering stage  318 . Other variations of encoder  300  can be used to encode the input video stream  302 . 
     When the input video stream  302  is presented for encoding, a frame (e.g., frame  208 ) within the input video stream  302  can be processed full-frame, by units of macroblocks, or by any other segment of pixels in the frame. At the intra/inter prediction stage  304 , blocks can be encoded using intra-frame prediction (within a single frame) or inter-frame prediction (from frame to frame). In either case, a prediction block can be formed. In the case of intra-prediction, a prediction block can be formed from prediction samples in the current frame that have been previously encoded and reconstructed. In the case of inter-prediction, a prediction block can be formed from prediction samples in one or more previously constructed reference frames. 
     Intra/inter prediction stage  304  can include a selective prediction signal filtering stage  305 . For example, in an implementation, a prediction block can be formed from prediction samples that are filtered using a filter. Exemplary implementations of prediction signal filtering that can be incorporated into stage  305 , such as technique  800 , are described later with respect to  FIG. 8 . 
     Next, still referring to  FIG. 3 , the prediction block can be subtracted from the current block at the intra/inter prediction stage  304  to produce a residual block (residual). The transform stage  306  transforms the residual into transform coefficients in, for example, the frequency domain. Examples of block-based transforms include the Karhunen-Loéve Transform (KLT), the Discrete Cosine Transform (“DCT”), and the Singular Value Decomposition Transform (“SVD”). In one example, the DCT transforms the block into the frequency domain. In the case of DCT, the transform coefficient values are based on spatial frequency, with the lowest frequency (DC) coefficient at the top-left of the matrix and the highest frequency coefficient at the bottom-right of the matrix. 
     The quantization stage  308  converts the transform coefficients into discrete quantum values, which are referred to as quantized transform coefficients or quantization levels. The quantized transform coefficients are then entropy encoded by the entropy encoding stage  310 . Entropy encoding can include the use of various techniques, such as formatting compressed bitstream  320  using run-length encoding (RLE) and zero-run coding. The entropy-encoded coefficients, together with the information used to decode the block, such as the type of prediction used, motion vectors, and quantizer value, are then output to the compressed bitstream  320 . 
     The reconstruction path in  FIG. 3  (shown by the dotted connection lines) can be used to ensure that both the encoder  300  and decoder  400  (described below) use the same reference frames to decode the compressed bitstream  320 . The reconstruction path performs functions that are similar to functions that take place during the decoding process that are discussed in more detail below, including dequantizing the quantized transform coefficients at the dequantization stage  312  and inverse transforming the dequantized transform coefficients at the inverse transform stage  314  to produce a derivative residual block (derivative residual). At the reconstruction stage  316 , the prediction block that was predicted at the intra/inter prediction stage  304  can be added to the derivative residual to create a reconstructed block. The loop filtering stage  318  can be applied to the reconstructed block to reduce distortion such as blocking artifacts. 
     An implementation of encoder  300  can include a group of filters, F 1 -Fn. In an implementation, compression can be optimized by filtering a set of pixels, such as a block of pixels  208 , in a given frame  206  in the reconstruction path with filters F 1 -Fn or filters F 1 -Fn and default filter Fs which may be a sharpening filter or other suitable default filter. In an implementation, the group of filters can be utilized in intra/inter prediction stage  304  using selective prediction signal filtering stage  305 . In various implementations, filtering can be used in the reconstruction loop, intra/inter prediction stage  304 , or both. In an implementation, selective prediction signal filtering stage  305  can be included in intra/inter prediction stage  304  and application of the group of filters can be omitted from the reconstruction path (e.g., performance measurement stage  317  and/or loop filtering stage  318  can be omitted from encoder  300 ) so that the unfiltered data can be retained as an alternative predictor for current or future blocks. 
     Compressed bitstream  320  may include frames  204  that contain residual blocks. Because prediction blocks are subtracted from current blocks at intra/inter prediction stage  204  to form residual blocks, residual blocks can improve compression by reducing the number of bits used to represent frames in compressed bitstream  320 . One way to reduce an amount of bits needed to represent the residual blocks is to improve the accuracy of prediction at the intra/inter prediction stage  304 . 
     For example, in an implementation, the accuracy of prediction at stage  304  can be improved by a performance measurement stage  317  that can select between multiple filter settings for a given set of pixels at loop filter  318  depending on the characteristics of the set of pixels. In addition to improving accuracy, selecting between multiple filter settings can also improve compression. For example, performance measurement stage  317  can compare a performance measurement of a given macroblock after provisional application of a filter with a performance measurement of that same macroblock prior to any filtration. The performance measurement may indicate quality, error, compression characteristics or a metric that takes into account quality, error and compression characteristics. Based on the results of such a comparison, encoder  300  may select zero, one or multiple filters from the group of filters F 1 -Fn to be used for loop filtering at stage  318 . Encoder  300  can select only the filters from F 1 -Fn that result in an improved performance measurement that exceeds the initial performance measurement for a particular block. 
     An improved performance measurement exceeds an initial performance measurement if its value is closer to a desired result. A desired result is typically a result in which a video signal is transmitted with higher quality or lower bandwidth or with greater reliability. Depending on the performance measurement, a measurement that exceeds another measurement could be numerically higher or lower than the other measurement. A performance measurement can be any metric used to indicate characteristics for a set of pixels. Rate distortion for example, is a metric that is a function of both error rate and coding efficiency. Customizing filtration on a macroblock by macroblock basis based on a performance measurement can result in a more robust and accurate prediction at intra/inter prediction stage  304 . These and other implementations are described herein with respect to  FIGS. 5-8 . 
     Other variations of encoder  300  can be used to encode the compressed bitstream  320 . For example, a non-transform based encoder can quantize the residual signal directly without the transform stage  306 . Various forms of error testing, error correction and filtering can be implemented in the reconstruction loop. In an implementation, performance measurement stage  317  can be omitted and/or can be incorporated into loop filtering stage  318 . In an implementation, an encoder can have the quantization stage  308  and the dequantization stage  312  combined into a single stage. 
     The encoding process shown in  FIG. 3  can include two iterations or “passes” of processing the video data. The first pass can be carried out by encoder  300  using an encoding process that is less computationally intensive which gathers and stores information about input video stream  302  for use in the second pass. In the second pass, encoder  300  can use this information to optimize final encoding of compressed bitstream  320 . For example, encoder  300  may use this information to select parameters for encoding, locating key-frames, selecting coding modes used to encode macroblocks such as blocks  208  and allocating the number of bits to each frame. The output of the second pass can be final compressed bitstream  320 . 
       FIG. 4  is a block diagram of a decoder  400  in accordance with an implementation of this disclosure. Decoder  400  can be implemented, for example, in receiving station  16  by providing a computer software program stored in memory  26  or storage  36 . The computer software program can include machine instructions that, when executed by CPU  24 , cause receiving station  16  to decode video data in the manner described in  FIG. 4 . Decoder  400  can also be implemented as hardware (e.g., an ASIC or FPGA) included in a computing device. 
     Decoder  400 , similar to the reconstruction path of encoder  300  discussed above, includes in one example the following stages to perform various functions to produce an output video stream  418  from a compressed bitstream  402  (e.g., compressed bitstream  320 ): an entropy decoding stage  404 , a dequantization stage  406 , an inverse transform stage  408 , an intra/inter prediction stage  410 , a reconstruction stage  412 , a loop filtering stage  414  and a deblocking filtering stage  416 . Other variations of decoder  400  can be used to decode the compressed bitstream  402 . 
     When the compressed bitstream  402  is presented for decoding, the data elements within the compressed bitstream  402  can be decoded by the entropy decoding stage  404  (using, for example, Context Adaptive Binary Arithmetic Decoding) to produce a set of quantized transform coefficients. The dequantization stage  406  dequantizes the quantized transform coefficients, and the inverse transform stage  408  inverse transforms the dequantized transform coefficients to produce a derivative residual. Using header information decoded from the compressed bitstream  402 , decoder  400  can use the intra/inter prediction stage  410  to create a prediction block. At the reconstruction stage  412 , the prediction block can be added to the derivative residual to create a reconstructed block. The loop filtering stage  414  can be applied to the reconstructed block to reduce blocking artifacts. The deblocking filtering stage  416  can be applied to the reconstructed block to reduce blocking distortion, and the result is output as the output video stream  418 . 
     Other variations of decoder  400  can be used to decode the compressed bitstream  402 . For example, decoder  400  can produce the output video stream  418  without the deblocking filtering stage  416 . Furthermore, for a decoder  400  that decodes a bitstream sent from encoder  300  as shown in  FIG. 3 , the decoder  400  can include thresholding, error testing and selectable loop filtering in the feedback loop to intra/inter prediction stage  410  to create the same reconstructed macroblock that was created at encoder  300 . Decoder  400  can also include filtering in inter/intra prediction stage  410 . 
     In an implementation, selecting a subset of pixels, taking a performance measurement of that subset and selecting filters for loop filtration can occur according to the flowchart of a technique  500  for performance measurement shown in  FIG. 5 . Technique  500  can be carried out, for example, by CPU  24  executing instructions stored in memory  26  of transmitting station  12  or receiving station  16 . Technique  500  or aspects thereof can be incorporated, for example, into performance measurement stage  317  or intra/inter prediction stage  304  of encoder  300 . 
     At step  504 , a set of pixels are selected. The set of selected pixels and can be an entire frame of pixels, a macroblock of pixels, or any other segment or number of pixels derived from a reconstructed frame assembled at reconstruction stage  412 . One example of an image segment or set of pixels is a macroblock of pixels  600  depicted in  FIG. 6 . At step  532 , the reconstructed image segment or set of pixels is measured for an initial performance measurement. The initial performance measurement measures some indicator of quality or error such as differences between an original set of pixels as constituted prior to encoding  300  and the reconstructed version of the original set of pixels at reconstruction stage  316 . During encoding, transform stage  306  and quantization stage  308  can create errors between a frame in input video stream  302  and the reconstructed version of that same frame at reconstruction stage  316 . An initial performance measurement may measure these errors or other errors related to a reconstructed frame. The performance measurement itself can be a sum of squares error, a mean squared error, or various other suitable measurements of error. The initial performance measurement can also be a calculation such as rate distortion, which takes into account an error measurement as well as coding efficiency. 
     Once an initial performance measurement has been determined for a particular set of pixels at step  532 , the performance measurement for that set of pixels is stored. For example at step  502 , a variable, here called base best rd, is initialized to the initial performance measurement for the set of pixels selected at step  504 . Once the variable base best rd has been initialized, the first filter denoted by variable n is selected at step  508 . As depicted in  FIG. 5 , each time a filter n is selected, process  520  shown by a dashed line box is engaged. When process  520  is complete, step  506  determines if all of the n filters have been selected. If all of the n filters have not been selected, step  508  increments n and selects the next filter. If all of the n filters have been selected, step  534  determines if there are any additional macroblocks that must undergo the process depicted in  FIG. 5 . If any of the k macroblocks remain, step  504  increments k and selects the next macroblock. If no macroblocks remain, at step  526  the results of process  520  are implemented at loop filter  318 . 
     Within process  520 , the filter selected at step  508  is applied to the particular set of pixels selected at step  504 . At step  530 , the filter n is applied to macroblock k, where filter n engages each pixel in macroblock k according to, for example, technique  700  as shown in  FIG. 7 . During technique  700 , each pixel in the set of pixels in macroblock k is analyzed in a predetermined order such as, for example, raster scan order or any other suitable order. When a pixel is engaged at step  702 , that pixel can be considered a “target pixel.” Data is retrieved from pixels in the region of the target pixel to make a determination or calculation with respect to a given target pixel. Specifically, data from a filter dependent region of pixels surrounding a target pixel is collected. For example, each pixel in the filter dependent region of pixels contains data related to how each pixel will appear when displayed, such as luma or chroma data represented by a number as depicted in  606 . Based on this data, technique  700  determines if the target pixel should be filtered or bypassed without filtration at step  704 . Process  520  is only an exemplary embodiment. 
     Referring to how threshold determinations are made, the determination at step  704  is made by comparing data from the filter dependent region of pixels  602  surrounding a target pixel  604  and comparing that data with a threshold or strength setting. The terms threshold and strength setting may be used interchangeably. Each filter F 1 -Fn may use a different type of threshold criteria. For example, step  704  may average all pixels in the filter dependent region of pixels to determine if they differ in value from the target pixel by less than a threshold value. 
     Step  704  may select filters that fall above or below a particular threshold criteria. In another exemplary embodiment, step  704  may indicate filter F 1  should be applied to a given pixel if the statistical variance of the pixels in the filter dependent region is below a threshold value. The statistical variance threshold criteria may be less computationally intensive than the target pixel differential approach as fewer computations per pixel are required. Accordingly, the statistical variance approach may be used for filters with a large amount of taps, such as long blur filters. 
     Once a threshold determination is made at step  704 , process  700  will either filter the target pixel at step  706  or pass through the target pixel without filtration at step  708 . In either case, the next step is to move to the next pixel at step  710 . In some embodiments, this process will continue until all pixels in the set of pixels selected at step  504  have received a threshold determination for the filter selected at step  508 . 
     By way of example, filter F 1  may be a one dimensional filter such as a one dimensional finite impulse response (FIR) filter with 3 taps and weights of (1, 3, 1) designed to be applied in the horizontal and vertical directions about a target pixel, for example, as shown in  FIG. 6B . Because of the properties of exemplary filter F 1 , the filter dependent region of pixels forms a cross section of pixels  602  including a row of 3 pixels centered at target pixel  604  and a column of 3 pixels centered at target pixel  604 . When an n-tap filter is one dimensional and is designed to be applied in the horizontal and vertical directions, the filter dependent region will contain 2*n pixels and will form a cross section centered at the target pixel as shown in  602 . 
     Additionally, filter F 2 , may be a one dimensional FIR filter with 5 taps and weights of (1, 1, 4, 1, 1) designed to be applied in horizontal and vertical directions to a target pixel, for example as shown in  FIG. 6C . Filters F 1 -Fn can also be two dimensional square filters that form a block of pixels about a target pixel or any other type of filter. Each filter selection can have design advantages and disadvantages. For example, a threshold determination for a two dimensional filter will require more calculations than a one dimensional filter applied in the horizontal and vertical directions because the filter dependent region of pixels is larger. Filters F 1 -Fn may contain various other types of filters such as one or two dimensional filters, sharpening filters, blurring filters, linear filters, edge detecting filters, Gaussian filters, Laplacian filters, embossing filters, edge sharpening filters, or any other image processing filters with any number of taps or weights. In one exemplary embodiment, filters F 1 -Fn include one dimensional FIR filters with taps and weights of (1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1), (1, 1, 4, 1, 1) and (−1, 3, −1). In one exemplary embodiment, the (−1, 3, −1) filter is a default sharpening filter that is applied to all pixels in a set of pixels, such as a macroblock of pixels, at step  530  without determining whether each pixel in the set of pixels should be filtered or passed through without filtration at step  706 . 
     In addition to the fact that each filter in F 1 -Fn may have a different threshold criteria, process  520  in  FIG. 5  can also alter the threshold value for each filter selected at step  508  so that a given filter is provisionally applied to a given set of pixels at multiple threshold values. For example, filter F 1  may use statistical variance as its threshold criteria. Filter F 1  may also have several different statistical variance values or strength settings, each of which is applied to the given set of pixels at step  530 . Specifically, once a first threshold value or strength setting is used at step  530  and the set of pixels undergo a second performance measurement at step  510 , a new threshold value or strength setting is received at step  516 . Each filter may have any number of strength settings. The process of determining and applying new strength settings may repeat until all strength settings have been measured for performance. Alternatively, process  520  may discontinue the process of receiving new strength settings if, for example, rate distortion measurements at step  510  indicate worsening rate distortion measurements for a predetermined number of measurements. 
       FIG. 6A  is a schematic diagram of a set of pixels, a filter dependent region of pixels using one type of filter, and a target pixel in accordance with an implementation of this disclosure and  FIG. 6B  is a schematic diagram of filtering a target pixel using one type of filter in accordance with an implementation of this disclosure. The selected set of pixels selected at step  504  is shown as macroblock  600 . Within technique  700 , target pixel  604  is selected at step  702  while cross section  602  is the filter dependent region of pixels from which data is taken to filter target pixel  604 . The target pixel shown in  6 B has a value of 60 while the values of the remaining pixels in the filter dependent region of pixels are 42, 46, 56 and 55. Steps  608  and  610  show one aspect of the filtering process. Selectable filters F 1 -Fn can be of any type or dimension. One type of filter can be a one dimensional FIR filter applied in the horizontal and vertical directions, for example. The filter may be applied horizontally and then vertically or vertically and then horizontally. These filters are also known as kernels and contain an array of values with one element in the array designated as origin of the kernel. The origin of kernels  608  and  610 , for example, is 3. The origin of the kernel corresponds to the pixel that will be affected by neighboring pixels in the kernel, which is the target pixel. 
     In  FIG. 6B , origin  3  corresponds to target pixel i in step  704 . In one embodiment, for example, if it is determined that any of the values  42 ,  46 ,  55  or  56  differ from the center pixel by less than a predetermined threshold at step  704 , the target pixel with a value of 60 will be filtered. If the values are more than a predetermined threshold, the pixel will pass through the filter without filtration. Accordingly, depending on the strength setting determined at step  516 , the number of pixels actually filtered in a given set of pixels for a given filter will change. Strength setting alteration step  516  may increase or decrease the strength setting or threshold value by a predetermined amount. To filter a target pixel, a convolution or correlation can be performed between the kernel and the filter dependent region of pixels  602  surrounding the target pixel  604 . Convolutions and correlations calculate a weighted average of all the pixels in the filter dependent region  602 . The resulting weighted average is used to replace the original target pixel value. As a result the target pixel value is altered or filtered based on the pixels in the filter dependent region surrounding it. 
       FIG. 6C  is a schematic diagram of a set of pixels, a filter dependent region of pixels using another type of filter, and a target pixel in accordance with an implementation of this disclosure and  FIG. 6D  is a schematic diagram of filtering a target pixel using another type of filter in accordance with an implementation of this disclosure.  FIGS. 6C and 6D  are analogous to  FIGS. 6A and 6B  and show a different filter having taps of (1,1,4,1,1) instead of (1,3,1). Included in  FIGS. 6C and 6D  is a target pixel  620 , cross section  618  of a filter dependent region, and filter area  612  given by kernels  614  and  616 . 
     Once a threshold determination has been made for all pixels in the set of pixels such that each pixel has either been filtered at step  706  or passed through at step  708 , a second performance measurement can be taken, such as rate distortion, for the set of pixels at step  510 . At step  512 , it is determined whether the second performance measurement from step  510  is less than the initial performance measurement determined at step  532 . If the second performance measurement after filtration at  530  is less than the initial performance measurement, variable best rd is updated with the new second performance measurement information. Furthermore, for each filter entering process  520 , the filters can be measured for performance for each of any number of strength settings determined at step  516  as discussed previously. Although process  520  depicts an implementation where a performance rate distortion measurement is used, other performance measurements can be used. 
     In an implementation, each time a strength setting results in a performance measurement that exceeds previous measurements, the best rd variable is updated at step  514  and the current filter n and filter strength i is saved at step  518 . Once the filters for all pixels in the set of pixels has gone through process  520  as indicated by step  534 , information associated with the filter n and strength i having the best performance measurement can be forwarded to loop filter stage  318  at step  526 . At loop filter stage  318 , pixels can be filtered using the filter and filter strength forwarded by performance measuring stage  317  at a strength setting indicated by performance measuring stage  317 . 
     The current filter n and filter strength i can be stored for transmission to be used at decoder  400  to recreate the same reconstructed and filtered image segment that was created at encoder  300 . It should also be noted that in order to properly decode frames created at encoder  300 , decoder  400  should implement a similar decoding path as the reconstruction path implemented by encoder  300 . 
     The above description of technique  500  describes some exemplary implementations of performance measurement and loop filtration and other implementations of technique  500  are available, including those that include additional stages, remove certain stages, modify certain stages, split certain stages, and/or combine certain stages. In an implementation, stage  526  can be moved to be between stages  506  and  534  so that filter n and strength i is applied on a per macroblock k basis. 
     In an implementation, technique  500  can be adjusted to identify more than one filter and filter strength. For example, a filter n evaluated by process  520  can incorporate the use of two or more filters in sequence. In another example, process  520  can be altered to select a filter and then select one or more additional filters based on performance measurements of the additional filters based on an application of that filter to pixel values filtered by the selected filter. Accordingly, depending on results from stage  317 , each set of pixels or macroblock  208  in frame  206  can have between zero and n filters implemented at loop filter stage  318 . 
       FIG. 8  is a flow chart of a technique  800  for selective prediction signal processing in accordance with an implementation of this disclosure. Technique  800  can be implemented, for example, within intra/inter prediction stage  304  of encoder  300 . Technique  800  can be performed, for example, with respect to a current block in a frame. In an implementation, technique  800  begins by initializing variables at stage  802 . For example, a variable indicating a best performance measurement (RD BEST ) can be initialized to an initial value, such as a rate distortion value that is greater than any expected rate distortion value generated by technique  800 . As another example, variables indicating a best identified mode (MODE BEST ) and a best identified filter state (FILTER) can also be initialized. 
     At stage  804 , a current mode X can be selected from available prediction modes. Available prediction modes for technique  800  can include all prediction modes included in encoder  300  or a subset thereof. For example, in various implementations, available prediction modes can include one of all inter-prediction modes, all intra-prediction modes, or both. 
     At stage  806 , a performance measurement (e.g. rate distortion) for the current mode X without filtering (RD X,OFF ) is determined. To determine the performance metric, the current mode X can be used to identify prediction samples for predicting the current block, comparing the prediction samples to the current block, and determining the metric using the comparison. The identified prediction samples are not filtered at stage  806 . In an implementation, determining the performance metric can include considering a number of bits needed to encode indications of mode X and the filter selection (e.g., FILTER=0) into the encoded bitstream. The performance measurement RD X,OFF  is compared to the best rate distortion value RD BEST  at stage  808 . If RD X,OFF  is less than RD BEST , control passes to stage  810 . 
     At stage  810 , the best identified mode (MODE BEST ) is set to the current mode X, the best rate distortion value (RD BEST ) is set to RD X,OFF , and the filter state (FILTER) is set to 0. After stage  810 , control passes to stage  812 . Alternatively, if RD X,OFF  is greater or equal than RD BEST , control passes to stage  812  from stage  808 . 
     At stage  812 , a performance measurement (e.g. rate distortion) for the current mode X with filtering (RD X,ON ) is determined. To determine the performance metric, the current mode X can be used to identify prediction samples for predicting the current block. The identified prediction samples can then be filtered, for example, by using a pre-determined filter. The filtering of the prediction samples can in addition or alternatively use techniques such as adaptations of those described with respect to  FIGS. 5, 6A -D, and/or  7 . The filtered prediction samples can be compared to the current block and the performance metric can be determined using the comparison. In an implementation, determining the performance metric can include considering a number of bits needed to encode indications of mode X and the filter selection (e.g., FILTER=1) into the encoded bitstream. 
     The performance measurement RD X,ON  is compared to the best rate distortion value RD BEST  at stage  814 . If RD X,ON  is less than RD BEST , control passes to stage  816 . At stage  816 , the best identified mode (MODE BEST ) is set to the current mode X, the best rate distortion value (RD BEST ) is set to RD X,ON , and the filter state (FILTER) is set to 1. After stage  816 , control passes to stage  818 . Alternatively, if RD X,ON  is greater or equal than RD BEST , control passes to stage  818  from stage  814 . 
     At stage  818 , a determination is made as to whether all available prediction modes have been tested (e.g., whether each available prediction mode has been processed through stages  804  to  816 ). If not all available prediction modes have been tested, control passes to stage  804 , where a new current mode X is selected from remaining available prediction modes. Otherwise, control passes to stage  820 , where a residual is determined using the MODE BEST  and FILTER settings determined by technique  800 . In other words, a residual is generated using the combination of mode and filter that produces a smallest (e.g., best) performance measurement (e.g., rate distortion). 
     Following stage  820  (not shown), MODE BEST  and FILTER can be encoded into the compressed bitstream along with the generated residual, for example, by use of probability encoding techniques by entropy encoding stage  310 . For example, FILTER can be entropy encoded using a binary flag or a tri-state flag. In an implementation using a binary flag, a flag (e.g., FILTER) can be encoded for each block (e.g., using a BoolCoder) based on a encoding probability (pred_filter_prob) that is generated, for example, based on a count of number of blocks where the filter is disabled (pred_filter_off_count) and a number of blocks where the filter is enabled (pred_filter_on_count), such as shown with respect to equation 1: 
     
       
         
           
             
               
                 
                   
                     pred_filter 
                     ⁢ 
                     _prob 
                   
                   = 
                   
                     
                       pred_filter 
                       ⁢ 
                       _off 
                       ⁢ 
                       _count 
                       * 
                       255 
                     
                     
                       
                         pred_filter 
                         ⁢ 
                         _off 
                         ⁢ 
                         _count 
                       
                       + 
                       
                         pred_filter 
                         ⁢ 
                         _on 
                         ⁢ 
                         _count 
                       
                     
                   
                 
               
               
                 
                   [ 
                   
                     Equation 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     1 
                   
                   ] 
                 
               
             
           
         
       
     
     The value of pred_filter_prob can be encoded into the compressed bitstream at the frame level and can be used to probabilistically encode the binary flag FILTER for each block within the frame. In an implementation, pred_filter_prob can be encoded as an 8-bit literal value, using less than 8-bits based on a modeling algorithm, using a differential with a pred_filter_prob value encoded for a previous frame, or a combination thereof. 
     In an implementation using a tri-state flag, a mode can be encoded at the frame level (e.g., by entropy encoding stage  310  using probability encoding techniques such as BoolCoder) and can indicate, for example, whether filtering should be enabled for the entire frame (0), disabled for the entire frame (1), or signaled at a per-macroblock level (2). If the per-macroblock level (2) mode is utilized, the binary flag technique described above can be used to encode a binary flag for each macroblock. In a one-pass encoder, the pred_filter_prob for a previous frame can be utilized instead of the pred_filter_prob for the current frame, since the value for the current frame can be determined once the entire frame is processed. 
     The above description of technique  800  describes some exemplary implementations of selective prediction signal processing and other implementations of technique  800  are available, including those that include additional stages, remove certain stages, modify certain stages, split certain stages, and/or combine certain stages. A number of alternative implementations are possible, including, but not limited to, the use of one or more of the additional and/or alternative techniques described below. 
     In an implementation, the available prediction modes for encoding can include one or more intra-prediction modes. Prediction samples can be identified using an intra-prediction mode and can optionally be filtered once identified. Alternatively or additionally, the intra-prediction mode can identify prediction samples based on pixels that are filtered before the prediction samples are identified. In an example, blocks of pixels above and to the left of a current block being encoded can be filtered before prediction samples are identified. 
     In an implementation, more than one filter (e.g., filter type and/or filter strength) can be considered in conjunction with available prediction modes. For example, an optimized filter can be identified for each prediction mode, multiple filters can be identified for at least some prediction modes, multiple filters can be identified without respect to prediction mode, or a combination thereof. Some prediction modes can have one or more associated filter, based on, for example, the suitability of the associated filters for use with their respective prediction modes. Available filters can include high-pass, low-pass, thresholded, separable, or non-separable filters. For example, a thresholded filter can be configured to filter a pixel only if the pixel to be filtered has adjoining pixels that have similar characteristics in an effort to preserve edges within the frame. 
     In the event that multiple filters are considered, an indication of the type and/or strength of filter used can be encoded into the compressed bitstream to enable a decoder to apply the same filter and strength during decoding (e.g., in addition to or instead of the FILTER flag). Thus, a filter indicator can include a binary flag (e.g., FILTER), a tri-state flag, an indication of filter type and/or strength, or a combination thereof. 
     In an implementation, available prediction modes can be defined to include a determination of whether filtering is to be performed. In other words, the filter indicator can be included within the prediction mode (e.g. defined based on the prediction mode). 
     In an implementation, the available prediction modes for encoding can include one or more inter-prediction modes. Inter-prediction can include performing a candidate search for a reference block (e.g., prediction samples), and the identification of the reference block can include considering unfiltered candidate search locations, filtered candidate search locations, or a combination thereof. The resulting reference block can therefore be identified based on pre-filtered candidate search locations, candidate search locations without pre-filtering, or a combination thereof. The use of pre-filtered candidate search locations can be used in addition to or instead of filtering identified prediction samples. 
     In an implementation, the use of selective prediction signal processing can be used in lieu of sub pixel motion compensation. Sub pixel motion compensation can include filtering candidate reference blocks to estimate virtual pixel values at locations between pixels. Selective prediction signal processing can provide a similar benefit as sub pixel motion compensation, and thus can be used instead of sub pixel motion compensation to improve efficiency of encoding. 
     In an implementation, the use of selective prediction signal processing can be used in lieu of Average Reference (frame) Noise Reduction (ARNR) filtering or in combination with a reduced level of ARNR filtering. ARNR filtering can include calculating an average of pixel values over a number of frames (e.g., 20 successive frames). ARNR filtering can provide an alternative reference frame with reduced noise to be used for inter-prediction. Selective prediction signal processing can provide similar benefits as ARNR filtering. Reduced ARNR filtering can include reducing a number of frames used to generate ARNR filtering. 
     In an implementation, a filter strength and/or type selected for an inter prediction mode can be determined based on a motion vector selected for the inter prediction mode. The filter strength and/or type can be based on a magnitude of the motion vector. For example, a stronger filter strength can be used for larger motion vector magnitudes and a weaker filter strength can be used for smaller motion vector magnitudes. As another example, a motion blur filter can be selected for larger motion vector magnitudes to compensate for blurring and a weak filter can be selected for smaller motion vector magnitudes to preserve detail. The filter strength and/or type can also be based on a direction of the motion vector. For example, a blur filter can be applied in the direction of the motion vector to compensate for blurring occurring in the direction of movement. 
     In an implementation a filter indicator can be entropy encoded into the compressed bitstream using contextual techniques. For example, a filter indicator for a block can be encoded based on the filter indicator for adjoining blocks, such as the blocks above and to the left of the block. These and other implementations of technique  800  are possible, including variations and combinations of the various implementations described herein. 
       FIG. 9  is a flow chart of a technique  900  for decoding a compressed bitstream encoded using selective prediction signal processing in accordance with an implementation of this disclosure. Technique  900  can be implemented, for example, within intra/inter prediction stage  410  of decoder  400 . Technique  900  can be performed, for example, with respect to a current block in a frame. In an implementation, technique  900  begins by identifying a block (or other group of pixels) to be decoded at stage  902 . At stage  904 , a prediction mode used for encoding the identified block is decoded from the bitstream, using, for example, entropy decoding stage  404 . At stage  906 , a filter indicator (e.g., FILTER) is decoded from the bitstream, using, for example, entropy decoding stage  404 . At stage  908 , a residual is decoded from the bitstream, using, for example, entropy decoding stage  404 . 
     At stage  910 , prediction samples are identified using the decoded prediction mode. For example, the prediction mode can be an inter-prediction mode, and the decoded prediction mode can include a motion vector identifying a reference block having the prediction samples to be used for decoding. At stage  912 , a determination is made whether FILTER=1. If FILTER=1, the identified prediction samples are filtered at stage  914 . Next, and also if FILTER=0, control passes to stage  916 , where the block is reconstructed using the prediction samples or filtered prediction samples and the decoded residual. 
     The above description of technique  900  describes some exemplary implementations of decoding a compressed bitstream encoded using selective prediction signal processing. Other implementations of technique  900  are available, including those that include additional stages, remove certain stages, modify certain stages, split certain stages, and/or combine certain stages. A number of alternative implementations are possible, including, but not limited to, the use of techniques capable of decoding a bitstream encoded using alternative implementations of technique  800 , such as those described above. For example, the decoded filter indicator can include an indication of filter type and/or strength instead of a boolean indicator that filtering is to be performed and the indicated filter type and/or strength can be used to filter the prediction samples at stage  914 . As another example, the filter indication can be incorporated into the prediction mode and stage  904  can be omitted and stage  912  and  914  can be incorporated into stage  910 . 
     Accordingly, as can be understood from the description above, aspects of this disclosure add a processing stage within an intra/inter prediction stage (e.g.,  304 ). During this stage, a most appropriate coding mode can be selected for each group of pixels (individual, sub-blocks, macro-blocks or segments) within a frame. The coding mode can be selected from a set of coding modes based on minimizing one or more error metrics between an original value (or original data) and a predicted value (or predicted data). Intra-modes (such as DC_PRED) create the prediction value from data already encoded within the same frame, while inter-modes use data from one of a number of previously encoded reference frames, e.g., the last, golden or alternative reference frames. 
     In one implementation, the prediction data that is outputted as a result of applying a coding mode to reference frame data is filtered to create an alternative prediction block. The encoder can consider both the filtered and unfiltered prediction variants for each coding mode and can use a rate-distortion function, for example, to decide which mode and filter state (off/on) to use for a particular set of pixels; balancing the additional “cost” of signaling the filter state (off/on) against anticipated ensuing savings in encoding a reduced residual signal. 
     As an example, in one implementation, a motion compensation stage may result in a fractional pixel motion vector. Once the vector has been selected, a prediction is created from a designated reference frame using the selected motion vector. This prediction can be evaluated by computing the cost of encoding the residual error and adding the cost of signaling the state of the filter (off in this example) providing a first coding option. The filter can then be applied to the prediction signal and the evaluation process repeated, this time factoring in the cost of signaling that the filter should be enabled, to give a second coding option. The different filters can be understood as giving rise to new prediction modes (e.g., a “0,0 motion vector” mode and a new “0,0 motion vector plus filtering” mode). Accordingly, unfiltered data can be retained as an alternative for a current block or future blocks. Once various mode/filter combinations have been evaluated, the combination providing a best rate-distortion trade-off can be selected for the final encoding. 
     Further, as can be understood from the description above, the mode can be encoded and the state of the prediction filter for each group of pixels (e.g., each macroblock, segment, etc.) can be signaled. In one implementation, the signaling is accomplished by using a binary flag (which may be called, for example, prediction_filter_state). The binary flag can be encoded for each group of pixels (e.g., macroblock, segment, etc.) specifying whether the prediction filter is disabled (e.g., with a value of 0) or enabled (e.g., with a value of 1) for that group of pixels (e.g., macroblock, segment, etc.), for example. Other values may also be used. The binary flag can be encoded using the BoolCoder into the final output bitstream during an entropy encoding stage, e.g.,  310 . During mode selection, counts of the number of group of pixels (e.g., macroblocks, segments, etc.) where the filter is disabled (e.g., pred_filter_off_count) and enabled (e.g., pred_filter_on_count) can be maintained and used to compute the encoding probability, e.g., using Equation 1. The value of pred_filter_prob can be encoded into a bitstream at the frame level, e.g., as an 8-bit literal value. In alternative implementations, the value of pred_filter_prob is encoded differentially from the value in the previous frame, or in less than 8-bits, e.g., using a relevant modeling algorithm. 
     In one implementation, the signaling is accomplished using a tri-state flag (which may be called, for example, prediction_filter_mode). The tri-state flag can be encoded at the frame level signaling that the prediction filter should be turned off (e.g., with a value of 0) or on (e.g., with a value of 1) for all group of pixels in the current frame (e.g., all macroblocks in the current frame), or indicating that the decision will be signaled independently at the group of pixel-level, such as at the macroblock-level, (e.g., with a value of 2). In the latter case, individual prediction_filter_state flags can be encoded for each group of pixels (e.g., each macroblock) as per the signaling method described above in relation to the binary flag. During mode selection, the pred_filter_prob computed for a previous frame can be used to compute the cost of signaling the prediction_filter_state flags for each group of pixels (e.g., each macroblock), since the value for the current frame may only be known at the end of mode selection in certain implementations. Alternatively, a first-pass could determine an estimation of this probability that could subsequently be used during a second-pass encode. The prediction_filter_mode flag can be encoded at the frame level using the BoolCoder. 
     The operation of encoding can be performed in many different ways and can produce a variety of encoded data formats. The above-described embodiments of encoding or decoding may illustrate some exemplary encoding techniques. However, in general, encoding and decoding are understood to include any transformation or any other change of data whatsoever. 
     The use of the adjectives “first,” “second,” “third,” etcetera herein is not intended to infer any particular meaning regarding a relationship between elements (e.g., ordering, positioning, etc.) unless specifically indicated. For example, a first frame and a second frame of a video stream can refer to any two frames of the video stream and does not necessarily indicate that the first frame and the second frame are the first two frames of the video stream or that the first frame is located before the second frame. 
     The use of the adjectives “better,” “best,” etcetera with respect to elements herein is not intended to infer that a particular element is the best possible element or is better than all other possible elements. Instead, the adjectives “better” and “best” are intended to indicate the relative strength or ranking of an element as compared to one or more other known elements based on particular criteria that may or may not be the most advantageous possible criteria to determine said ranking or strength. 
     The words “example” or “exemplary” are used herein to mean serving as an example, instance, or illustration. Any aspect or design described herein as “example’ or “exemplary” is not necessarily to be construed as preferred or advantageous over other aspects or designs. Rather, use of the words “example” or “exemplary” is intended to present concepts in a concrete fashion. As used in this application, the term “or” is intended to mean an inclusive “or” rather than an exclusive “or”. That is, unless specified otherwise, or clear from context, “X includes A or B” is intended to mean any of the natural inclusive permutations. That is, if X includes A; X includes B; or X includes both A and B, then “X includes A or B” is satisfied under any of the foregoing instances. In addition, the articles “a” and “an” as used in this application and the appended claims should generally be construed to mean “one or more” unless specified otherwise or clear from context to be directed to a singular form. Moreover, use of the term “an embodiment” or “one embodiment” or “an implementation” or “one implementation” throughout is not intended to mean the same embodiment or implementation unless described as such. 
     The processors described herein can be any type of device, or multiple devices, capable of manipulating or processing information now-existing or hereafter developed, including, for example, optical processors, quantum and/or molecular processors, general purpose processors, special purpose processors, intellectual property (IP) cores, ASICS, programmable logic arrays, programmable logic controllers, microcode, firmware, microcontrollers, microprocessors, digital signal processors, memory, or any combination of the foregoing. In the claims, the terms “processor,” “core,” and “controller” should be understood as including any of the foregoing, either singly or in combination. Although a processor of those described herein may be illustrated for simplicity as a single unit, it can include multiple processors or cores. 
     In accordance with an implementation of the invention, a computer program application stored in non-volatile memory or computer-readable medium (e.g., register memory, processor cache, RAM, ROM, hard drive, flash memory, CD ROM, magnetic media, etc.) may include code or executable instructions that when executed may instruct or cause a controller or processor to perform methods discussed herein such as a method for performing a coding operation on video data using a computing device containing a plurality of processors in accordance with an implementation of the invention. 
     A computer-readable medium may be a non-transitory computer-readable media including all forms and types of memory and all computer-readable media except for a transitory, propagating signal. In an implementation, the non-volatile memory or computer-readable medium may be external memory. 
     Although specific hardware and data configurations have been described herein, note that any number of other configurations may be provided in accordance with implementations of the invention. Thus, while there have been shown, described, and pointed out fundamental novel features of the invention as applied to several implementations, it will be understood that various omissions, substitutions, and changes in the form and details of the illustrated implementations, and in their operation, may be made by those skilled in the art without departing from the spirit and scope of the invention. Substitutions of elements from one implementation to another are also fully intended and contemplated. The invention is defined solely with regard to the claims appended hereto, and equivalents of the recitations therein.