Patent Description:
Disclosed herein are an apparatus, a method and processor exectutable instructions (on a non-transitory computer-readable storage medium) for decoding using efficient context handling in arithmetic coding.

More specifically, the current application discloses an apparatus, a method and a non-transitory computer-readable storage medium comprising executable instructions, respectively according to appended independent claims <NUM>, <NUM> and <NUM>.

The description herein makes reference to the accompanying drawings wherein like reference numerals refer to like parts throughout the several views, and wherein:.

The invention is disclosed in <FIG> and <FIG> and in the corresponding parts of the description. The other parts of the description - except when disclosing elements referred to by said figures (and by the associated parts of the description) - are just meant to provide further examples, even if the expressions "implementation", "invention" or "embodiment" happen to be (inappropriately) used.

Video compression schemes may include breaking each image, or frame, into smaller portions, such as blocks, and generating an output bitstream using techniques to limit the information included for each block in the output. An encoded bitstream can be decoded to re-create the blocks and the source images from the limited information. Coding a video stream can include entropy coding, which is a lossless compression technique that may include substituting tokens, or codewords, for bit patterns, or symbols, in the output data stream. In some implementations, the token for a symbol may be determined based on context coefficients, such as the coefficient immediately to the left of the current coefficient, the coefficient immediately above the current coefficient, or a combination of both.

In some implementations, a decoder may store each decoded coefficient for a block in a context coefficient register for use in decoding subsequent coefficients. The size of the context coefficient register may be a function of the size of the coefficient matrix used for coding. For example, the coefficient matrix may be a NxM matrix, such as a 32x32 matrix, encoded using a non-contiguous coding order, such as the coding order partially shown in <FIG>, and the context coefficient register may include N*M coefficients, such as <NUM> (<NUM>*<NUM>=<NUM>) coefficients. In some implementations, each coefficient may be stored using B bits, such as <NUM> bits, and the size of the context coefficient register may be B*N*M bits, such as <NUM> bits (<NUM>*3bits).

In some implementations, video coding using efficient context handling in arithmetic coding includes using a reduced size context coefficient register, which may reduce resource utilization and improve timing in the decoder. Video coding using efficient context handling in arithmetic coding using a reduced size context coefficient register may include determining a scan order distance between a scan order location of a encoded coefficient and scan order locations of the corresponding context coefficients, and reading the corresponding context coefficient values from the location in the reduced size context coefficient register indicated by the corresponding distance. The size of the reduced size context coefficient register may be one less than the maximal scan order distance.

<FIG> is a diagram of a computing device <NUM> in which implementations of this disclosure may be incorporated. Computing device <NUM> as shown includes a communication interface <NUM>, a communication unit <NUM>, a user interface (UI) <NUM>, a processor <NUM>, a memory <NUM>, instructions <NUM>, and a power source <NUM>. As used herein, the term "computing device" includes any unit, or combination of units, capable of performing any method, or any portion or portions thereof, disclosed herein.

Computing device <NUM> may be a stationary computing device, such as a personal computer (PC), a server, a workstation, a minicomputer, or a mainframe computer; or a mobile computing device, such as a mobile telephone, a personal digital assistant (PDA), a laptop, or a tablet PC. Although shown as a single unit, any one or more elements of computing device <NUM> can be integrated into any number of separate physical units. For example, UI <NUM> and processor <NUM> can be integrated in a first physical unit and memory <NUM> can be integrated in a second physical unit.

Communication interface <NUM> can be a wireless antenna, as shown, a wired communication port, such as an Ethernet port, an infrared port, a serial port, or any other wired or wireless unit capable of interfacing with a wired or wireless electronic communication medium <NUM>.

Communication unit <NUM> can be configured to transmit or receive signals via wired or wireless medium <NUM>. For example, as shown, communication unit <NUM> is operatively connected to an antenna configured to communicate via wireless signals. Although not explicitly shown in <FIG>, communication unit <NUM> can be configured to transmit, receive, or both via any wired or wireless communication medium, such as radio frequency (RF), ultra violet (UV), visible light, fiber optic, wire line, or a combination thereof. Although <FIG> shows a single communication unit <NUM> and a single communication interface <NUM>, any number of communication units and any number of communication interfaces can be used.

UI <NUM> can include any unit capable of interfacing with a user, such as a virtual or physical keypad, a touchpad, a display, a touch display, a speaker, a microphone, a video camera, a sensor, or any combination thereof. UI <NUM> can be operatively coupled with processor <NUM>, as shown, or with any other element of computing device <NUM>, such as power source <NUM>. Although shown as a single unit, UI <NUM> may include one or more physical units. For example, UI <NUM> may include an audio interface for performing audio communication with a user, and a touch display for performing visual and touch based communication with the user. Although shown as separate units, communication interface <NUM>, communication unit <NUM>, and UI <NUM>, or portions thereof, may be configured as a combined unit. For example, communication interface <NUM>, communication unit <NUM>, and UI <NUM> may be implemented as a communications port capable of interfacing with an external touchscreen device.

Processor <NUM> can include any device or system capable of manipulating or processing a signal or other information now-existing or hereafter developed, including optical processors, quantum processors, molecular processors, or a combination thereof. For example, processor <NUM> can include a general purpose processor, a special purpose processor, a conventional processor, a digital signal processor (DSP), a plurality of microprocessors, one or more microprocessor in association with a DSP core, a controller, a microcontroller, an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a programmable logic array, programmable logic controller, microcode, firmware, any type of integrated circuit (IC), a state machine, or any combination thereof. As used herein, the term "processor" includes a single processor or multiple processors. Processor <NUM> can be operatively coupled with communication interface <NUM>, communication unit <NUM>, UI <NUM>, memory <NUM>, instructions <NUM>, power source <NUM>, or any combination thereof.

Memory <NUM> can include any non-transitory computer-usable or computer-readable medium, such as any tangible device that can, for example, contain, store, communicate, or transport instructions <NUM>, or any information associated therewith, for use by or in connection with processor <NUM>. The non-transitory computer-usable or computer-readable medium is, for example, a solid state drive, a memory card, removable media, a read only memory (ROM), a random access memory (RAM), any type of disk including a hard disk, a floppy disk, an optical disk, a magnetic or optical card, an application specific integrated circuits (ASICs), or any type of non-transitory media suitable for storing electronic information, or any combination thereof. Memory <NUM> can be connected to processor <NUM> through, for example, a memory bus (not explicitly shown).

Instructions <NUM> can include directions for performing any method, or any portion or portions thereof, disclosed herein. Instructions <NUM> can be realized in hardware, software, or any combination thereof. For example, instructions <NUM> may be implemented as information stored in memory <NUM>, such as a computer program, that is executed by processor <NUM> to perform any of the respective methods, algorithms, aspects, or combinations thereof, as described herein. Instructions <NUM>, or a portion thereof, may be implemented as a special purpose processor, or circuitry, that can include specialized hardware for carrying out any of the methods, algorithms, aspects, or combinations thereof, as described herein. Portions of instructions <NUM> can be distributed across multiple processors on the same machine or different machines or across a network such as a local area network, a wide area network, the Internet, or a combination thereof.

Power source <NUM> can be any suitable device for powering communication interface <NUM>. For example, power source <NUM> can include a wired power source; one or more dry cell batteries, such as nickel-cadmium (NiCd), nickel-zinc (NiZn), nickel metal hydride (NiMH), lithium-ion (Li-ion); solar cells; fuel cells; or any other device capable of powering communication interface <NUM>. Communication interface <NUM>, communication unit <NUM>, UI <NUM>, processor <NUM>, instructions <NUM>, memory <NUM>, or any combination thereof, can be operatively coupled with power source <NUM>.

Although shown as separate elements, communication interface <NUM>, communication unit <NUM>, UI <NUM>, processor <NUM>, instructions <NUM>, power source <NUM>, memory <NUM>, or any combination thereof, can be integrated in one or more electronic units, circuits, or chips.

<FIG> is a diagram of a computing and communications system <NUM> in accordance with this disclosure. Computing and communications system <NUM> may include one or more computing and communication devices 100A/100B/100C, one or more access points 210A/210B, one or more networks <NUM>, or a combination thereof. For example, computing and communication system <NUM> can be a multiple access system that provides communication, such as voice, data, video, messaging, broadcast, or a combination thereof, to one or more wired or wireless communicating devices, such as computing and communication devices 100A/100B/100C. Although for simplicity <FIG> shows three computing and communication devices 100A/100B/100C, two access points 210A/210B, and one network <NUM>, any number of computing and communication devices, access points, and networks can be used.

Each computing and communication device 100A/100B/100C can be, for example, a computing device, such as computing device <NUM> shown in <FIG>. For example, as shown, computing and communication devices 100A/100B may be user devices, such as a mobile computing device, a laptop, a thin client, or a smartphone, and communication device 100C may be a server, such as a mainframe or a cluster. Although computing and communication devices 100A/100B are described as user devices, and computing and communication device 100C is described as a server, any computing and communication device may perform some or all of the functions of a server, some or all of the functions of a user device, or some or all of the functions of a server and a user device.

Each computing and communication device 100A/100B/100C can be configured to perform wired or wireless communication. For example, at least one of computing and communication device 100A/100B/100C can be configured to transmit or receive wired or wireless communication signals and can include a user equipment (UE), a mobile station, a fixed or mobile subscriber unit, a cellular telephone, a personal computer, a tablet computer, a server, consumer electronics, or any similar device. Although each computing and communication device 100A/100B/100C is shown as a single unit, a computing and communication device can include any number of interconnected elements.

Each access point 210A/210B can be any type of device configured to communicate with a computing and communication device 100A/100B/100C, a network <NUM>, or both via wired or wireless communication links 180A/180B/180C. For example, an access point 210A/210B can include a base station, a base transceiver station (BTS), a Node-B, an enhanced Node-B (eNode-B), a Home Node-B (HNode-B), a wireless router, a wired router, a hub, a relay, a switch, or any similar wired or wireless device. Although each access point 210A/210B is shown as a single unit, an access point can include any number of interconnected elements.

Network <NUM> can be any type of network configured to provide services, such as voice, data, applications, voice over internet protocol (VoIP), or any other communications protocol or combination of communications protocols, over a wired or wireless communication link. For example, network <NUM> can be a local area network (LAN), wide area network (WAN), virtual private network (VPN), a mobile or cellular telephone network, the Internet, or any other means of electronic communication. Network <NUM> can use a communication protocol, such as the transmission control protocol (TCP), the user datagram protocol (UDP), the internet protocol (IP), the real-time transport protocol (RTP) the Hyper Text Transport Protocol (HTTP), or a combination thereof.

Computing and communication devices 100A/100B/100C can communicate with each other via network <NUM> using one or more a wired or wireless communication links, or via a combination of wired and wireless communication links. As shown, for example, computing and communication devices 100A/100B can communicate via wireless communication links 180A/180B, and computing and communication device 100C can communicate via a wired communication link 180C. Any of computing and communication devices 100A/100B/100C may communicate using any wired or wireless communication link, or links. For example, a first computing and communication device 100A can communicate via a first access point 210A using a first type of communication link, a second computing and communication device 100B can communicate via a second access point 210B using a second type of communication link, and a third computing and communication device 100C can communicate via a third access point (not shown) using a third type of communication link. Similarly, access points 210A/210B can communicate with network <NUM> via one or more types of wired or wireless communication links 230A/230B. Although <FIG> shows computing and communication devices 100A/100B/100C in communication via network <NUM>, computing and communication devices 100A/100B/100C can communicate with each other via any number of communication links, such as a direct wired or wireless communication link.

Other implementations of computing and communications system <NUM> are possible. For example, in an implementation, network <NUM> can be an ad-hock network and can omit one or more of access points 210A/210B. Computing and communications system <NUM> may include devices, units, or elements not shown in <FIG>. For example, computing and communications system <NUM> may include many more communicating devices, networks, and access points.

<FIG> is a diagram of a video stream <NUM> for use in encoding and decoding in accordance with this disclosure. Video stream <NUM>, such as a video stream captured by a video camera or a video stream generated by a computing device, includes a video sequence <NUM>. Video sequence <NUM> includes a sequence of adjacent frames <NUM>. Although three adjacent frames <NUM> are shown, video sequence <NUM> can include any number of adjacent frames <NUM>. Each frame <NUM> from adjacent frames <NUM> may represent a single image from video stream <NUM>. A frame <NUM> may include blocks <NUM>. Although not shown in <FIG>, a block can include pixels. For example, a block can include a 16x16 group of pixels, an 8x8 group of pixels, an 8x16 group of pixels, or any other group of pixels. Unless otherwise indicated herein, the term 'block' can include a superblock, a macroblock, a segment, a slice, or any other portion of a frame. A frame, a block, a pixel, or a combination thereof can include display information, such as luminance information, chrominance information, or any other information that can be used to store, modify, communicate, or display video stream <NUM> or a portion thereof.

<FIG> is a block diagram of an encoder <NUM> in accordance with this disclosure. Encoder <NUM> can be implemented in a device, such as computing device <NUM> shown in <FIG> or computing and communication devices 100A/100B/100C shown in <FIG>, as a computer software program stored in a data storage unit, such as memory <NUM> shown in <FIG>. The computer software program can include machine instructions that may be executed by a processor, such as processor <NUM> shown in <FIG>, and cause the device to encode video data as described herein. Encoder <NUM> can be implemented as specialized hardware included, for example, in computing device <NUM>.

Encoder <NUM> can encode an input video stream <NUM>, such as video stream <NUM> shown in <FIG> to generate an encoded (compressed) bitstream <NUM>. In some implementations, encoder <NUM> may include a forward path for generating compressed bitstream <NUM>. The forward path may include an intra/inter prediction unit <NUM>, a transform unit <NUM>, a quantization unit <NUM>, an entropy encoding unit <NUM>, or any combination thereof. In some implementations, encoder <NUM> may include a reconstruction path (indicated by the broken connection lines) to reconstruct a frame for encoding of further blocks. The reconstruction path may include a dequantization unit <NUM>, an inverse transform unit <NUM>, a reconstruction unit <NUM>, a loop filtering unit <NUM>, or any combination thereof. Other structural variations of encoder <NUM> can be used to encode video stream <NUM>.

For encoding video stream <NUM>, each frame within video stream <NUM> can be processed in units of blocks. Thus, a current block may be identified from the blocks in a frame, and the current block may be encoded.

At intra/inter prediction unit <NUM>, the current block can be encoded using either intra-frame prediction, which may be within a single frame, or inter-frame prediction, which may be from frame to frame. Intra-prediction may include generating a prediction block from samples in the current frame that have been previously encoded and reconstructed. Inter-prediction may include generating a prediction block from samples in one or more previously constructed reference frames. Generating a prediction block for a current block in a current frame may include performing motion estimation to generate a motion vector indicating an appropriate reference block in the reference frame.

Intra/inter prediction unit <NUM> may subtract the prediction block from the current block (raw block) to produce a residual block. Transform unit <NUM> may perform a block-based transform, which includes transforming the residual block into transform coefficients in, for example, the frequency domain. Examples of block-based transforms include the Karhunen-Loève Transform (KLT), the Discrete Cosine Transform (DCT), and the Singular Value Decomposition Transform (SVD). In an example, the DCT may include transforming a block into the frequency domain. The DCT may include using transform coefficient values based on spatial frequency, with the lowest frequency (i.e., DC) coefficient at the top-left of the matrix and the highest frequency coefficient at the bottom-right of the matrix.

Quantization unit <NUM> may convert the transform coefficients into discrete quantum values, which are referred to as quantized transform coefficients or quantization levels. The quantized transform coefficients can be entropy encoded by entropy encoding unit <NUM> to produce entropy-encoded coefficients. Entropy encoding can include using a probability distribution metric. The entropy-encoded coefficients and information used to decode the block, which may include the type of prediction used, motion vectors, and quantizer values, can be output to compressed bitstream <NUM>. Compressed bitstream <NUM> can be formatted using various techniques, such as run-length encoding (RLE) and zero-run coding.

The reconstruction path can be used to maintain reference frame synchronization between encoder <NUM> and a corresponding decoder, such as decoder <NUM> shown in <FIG>. The reconstruction path may be similar to the decoding process discussed below, and includes dequantizing the quantized transform coefficients at dequantization unit <NUM> and inverse transforming the dequantized transform coefficients at inverse transform unit <NUM> to produce a derivative residual block. Reconstruction unit <NUM> may add the prediction block generated by intra/inter prediction unit <NUM> to the derivative residual block to create a reconstructed block. Loop filtering unit <NUM> can be applied to the reconstructed block to reduce distortion, such as blocking artifacts.

Other variations of encoder <NUM> can be used to encode compressed bitstream <NUM>. For example, a non-transform based encoder <NUM> can quantize the residual block directly without transform unit <NUM>. In some implementations, quantization unit <NUM> and dequantization unit <NUM> may be combined into a single unit.

<FIG> is a block diagram of a decoder <NUM> in accordance with implementations of this disclosure. Decoder <NUM> can be implemented in a device, such as computing device <NUM> shown in <FIG> or computing and communication devices 100A/100B/100C shown in <FIG>, as a computer software program stored in a data storage unit, such as memory <NUM> shown in <FIG>. The computer software program can include machine instructions that may be executed by a processor, such as processor <NUM> shown in <FIG>, and cause the device to decode video data as described herein. Decoder <NUM> can be implemented as specialized hardware included, for example, in computing device <NUM>.

Decoder <NUM> may receive a compressed bitstream <NUM>, such as compressed bitstream <NUM> shown in <FIG>, and may decode compressed bitstream <NUM> to generate an output video stream <NUM>. Decoder <NUM> may include an entropy decoding unit <NUM>, a dequantization unit <NUM>, an inverse transform unit <NUM>, an intra/inter prediction unit <NUM>, a reconstruction unit <NUM>, a loop filtering unit <NUM>, a deblocking filtering unit <NUM>, or any combination thereof. Other structural variations of decoder <NUM> can be used to decode compressed bitstream <NUM>.

Entropy decoding unit <NUM> decodes data elements within the compressed bitstream <NUM> using, for example, Context Adaptive Binary Arithmetic Decoding, to produce a set of quantized transform coefficients. Dequantization unit <NUM> can dequantize the quantized transform coefficients, and inverse transform unit <NUM> can inverse transform the dequantized transform coefficients to produce a derivative residual block, which may correspond with the derivative residual block generated by inverse transformation unit <NUM> shown in <FIG>. Using header information decoded from compressed bitstream <NUM>, intra/inter prediction unit <NUM> may generate a prediction block corresponding to the prediction block created in encoder <NUM>. At reconstruction unit <NUM>, the prediction block can be added to the derivative residual block to create a reconstructed block. Loop filtering unit <NUM> can be applied to the reconstructed block to reduce blocking artifacts. Deblocking filtering unit <NUM> can be applied to the reconstructed block to reduce blocking distortion, and the result may be output as output video stream <NUM>.

Other variations of decoder <NUM> can be used to decode compressed bitstream <NUM>. For example, decoder <NUM> can produce output video stream <NUM> without deblocking filtering unit <NUM>.

<FIG> is a block diagram of a representation of a portion <NUM> of a frame, such as frame <NUM> shown in <FIG>, in accordance with this disclosure. As shown, portion <NUM> includes four 64x64 blocks <NUM>, in two rows and two columns in a matrix or Cartesian plane. In some implementations, a 64x64 block may be a maximum coding unit, N=<NUM>. Each 64x64 block may include up to four 32x32 blocks <NUM>. Each 32x32 block may include up to four 16x16 blocks <NUM>. Each 16x16 block may include up to four 8x8 blocks <NUM>. Each 8x8 block <NUM> may include up to four 4x4 blocks <NUM>. Each 4x4 block <NUM> includes up to <NUM> pixels, which may be represented in four rows and four columns in each respective block in the Cartesian plane or matrix. The pixels may include information representing an image captured in the frame, such as luminance information, color information, and location information. In some implementations, a block, such as a 16x16-pixel block as shown, includes a luminance block <NUM> having luminance pixels <NUM> and two chrominance blocks <NUM>/<NUM>, such as a U or Cb chrominance block <NUM>, and a V or Cr chrominance block <NUM>. Chrominance blocks <NUM>/<NUM> include chrominance pixels <NUM>. For example, luminance block <NUM> includes 16x16 luminance pixels <NUM> and each chrominance block <NUM>/<NUM> includes 8x8 chrominance pixels <NUM> as shown. Although one arrangement of blocks is shown, any arrangement may be used. Although <FIG> shows NxN blocks, in some implementations, NxM blocks where N^M may be used. For example, 32x64 blocks, 64x32 blocks, 16x32 blocks, 32x16 blocks, or any other size blocks may be used. In some implementations, Nx2N blocks, 2NxN blocks, or a combination thereof may be used.

Ordered block-level coding includes coding blocks of a frame in an order, such as raster-scan order, wherein blocks may be identified and processed starting with a block in the upper left corner of the frame, or portion of the frame, and proceeding along rows from left to right and from the top row to the bottom row, identifying each block in turn for processing. For example, the 64x64 block in the top row and left column of a frame may be the first block coded, and the 64x64 block immediately to the right of the first block may be the second block coded. The second row from the top may be the second row coded, such that the 64x64 block in the left column of the second row is coded after the 64x64 block in the rightmost column of the first row.

Coding a block may include using quad-tree coding, which includes coding smaller block units within a block in raster-scan order. For example, the 64x64 block shown in the bottom left corner of the portion <NUM> in <FIG> may be coded using quad-tree coding wherein the top left 32x32 block is coded, then the top right 32xz32 block is coded, then the bottom left 32x32 block is coded, and then the bottom right 32x32 block is coded. Each 32x32 block may be coded using quad-tree coding wherein the top left 16x16 block is coded, then the top right 16x16 block is coded, then the bottom left 16x16 block is coded, and then the bottom right 16x16 block is coded. Each 16x16 block may be coded using quad-tree coding wherein the top left 8x8 block is coded, then the top right 8x8 block is coded, then the bottom left 8x8 block is coded, and then the bottom right 8x8 block is coded. Each 8x8 block may be coded using quad-tree coding wherein the top left 4x4 block is coded, then the top right 4x4 block is coded, then the bottom left 4x4 block is coded, and then the bottom right 4x4 block is coded. In some implementations, 8x8 blocks may be omitted for a 16x16 block, and the 16x16 block may be coded using quad-tree coding wherein the top left 4x4 block is coded, and then the other 4x4 blocks in the 16x16 block are coded in raster-scan order.

Video coding may include compressing the information included in an original, or input, frame by, for example, omitting some of the information in the original frame from a corresponding encoded frame. For example, coding may include reducing spectral redundancy, reducing spatial redundancy, reducing temporal redundancy, or a combination thereof.

Reducing spectral redundancy may include using a color model based on a luminance component (Y) and two chrominance components (U and V or Cb and Cr), which may be referred to as the YUV or YCbCr color model, or color space. Using the YUV color model, for example, includes using a relatively large amount of information to represent the luminance component of a portion of a frame and using a relatively small amount of information to represent each corresponding chrominance component for the portion of the frame. For example, a portion of a frame may be represented by a high resolution luminance component, such as 16x16 blocks of pixels, and by two lower resolution chrominance components, each of which represents the portion of the frame as an 8x8 block of pixels. A pixel may indicate a value, for example, a value in the range from <NUM> to <NUM>, and may be stored or transmitted using eight bits. Although this disclosure is described in reference to the YUV color model, any color model may be used.

Reducing spatial redundancy may include transforming a block into the frequency domain using, for example, a discrete cosine transform (DCT). For example, a unit of an encoder, such as transform unit <NUM> shown in <FIG>, may perform a DCT using transform coefficient values based on spatial frequency.

Reducing temporal redundancy may include using similarities between frames to encode a frame using a relatively small amount of data based on one or more reference frames, which are previously encoded, decoded, and reconstructed frames of the video stream. For example, a block or pixel of a current frame may be similar to a spatially corresponding block or pixel of a reference frame. A block or pixel of a current frame may be similar to block or pixel of a reference frame at a different spatial location, and reducing temporal redundancy thus includes generating motion information indicating the spatial difference, or translation, between the location of the block or pixel in the current frame and corresponding location of the block or pixel in the reference frame.

To reduce temporal redundancy, a block or pixel in a reference frame, or a portion of the reference frame, that corresponds with a current block or pixel of a current frame is identified. For example, a reference frame, or a portion of a reference frame stored in memory may be searched for the best block or pixel to use for encoding a current block or pixel of the current frame. In this way, a search identifies the block of the reference frame for which the difference in pixel values between the reference block and the current block is minimized. This is referred to as motion searching. The portion of the reference frame searched may be limited such that the search area includes, for example, a limited number of rows of the reference frame. Identifying the reference block may include calculating a cost function, such as a sum of absolute differences (SAD), between the pixels of the blocks in the search area and the pixels of the current block.

In some implementations, the spatial difference between the location of the reference block in the reference frame and the current block in the current frame is represented as a motion vector. The difference in pixel values between the reference block and the current block is commonly referred to as differential data, residual data, or as a residual block. Generating motion vectors may be referred to as motion estimation, and a pixel of a current block may be indicated based on location using Cartesian coordinates as fx,y. Similarly, a pixel of the search area of the reference frame may be indicated based on location using Cartesian coordinates as rx,y. A motion vector (MV) for the current block may be determined based on, for example, a SAD between the pixels of the current frame and the corresponding pixels of the reference frame.

Although motion-compensated partitioning is described herein with reference to matrix or Cartesian representation of a frame for clarity, a frame may be stored, transmitted, processed, or any combination thereof, in any data structure such that pixel values may be efficiently predicted for a frame or image. For example, a frame may be stored, transmitted, processed, or any combination thereof, in a two dimensional data structure such as a matrix as shown, or in a one dimensional data structure, such as a vector array. In an implementation, a representation of the frame, such as a two dimensional representation as shown, corresponds to a physical location in a rendering of the frame as an image. For example, a location in the top left corner of a block in the top left corner of the frame may correspond with a physical location in the top left corner of a rendering of the frame as an image.

The content captured within a block may include two or more areas that exhibit distinct spatial and temporal characteristics. For example, a frame may capture multiple objects moving in various directions and speeds, and a block may include an edge or object boundary. Block-based coding efficiency may be improved by partitioning blocks that include multiple areas with distinct characteristics into one or more partitions, which can be rectangular, including square, partitions, corresponding to the distinct content, and encoding the partitions rather than encoding each minimum coding unit independently.

A partitioning scheme may be selected from among multiple candidate partitioning schemes. For example, candidate partitioning schemes for a 64x64 coding unit may include rectangular size partitions ranging in sizes from 4x4 to 64x64, such as 4x4, 4x8, 8x4, 8x8, 8x16, 16x8, 16x16, 16x32, 32x16, 32xz32, 32x64, 64x32, or 64x64. In some implementations, partitioning includes a full partition search, which may include selecting a partitioning scheme by encoding the coding unit using each available candidate partitioning scheme and selecting the best scheme, such as the scheme that produces the least rate-distortion error. In other implementations, such as offline two-pass encoding, information regarding motion between frames is generated in a first coding pass, and then is utilized to select a partitioning scheme in a second coding pass. Techniques such as offline two-pass encoding and evaluating rate-distortion error, or other similar metrics, for each candidate partitioning scheme, may be time-consuming, and may utilize more than half of the encoding time. Where video conferencing or other content that includes a static background is encoded, for example, a partitioning scheme may be selected based on the difference between previous and current source frames.

Motion-compensated partitioning may identify a partitioning scheme more efficiently than full partition searching, offline two-pass encoding, or partitioning based on inter-frame differences. Motion-compensated partitioning includes, for example, identifying a partitioning scheme for encoding a current block, such as block <NUM>. In some implementations, identifying a partitioning scheme includes determining whether to encode the block as a single partition of maximum coding unit size, which may be 64x64 as shown, or to partition the block into multiple partitions, which corresponds with the sub-blocks, such as the 32x32 blocks <NUM> the 16x16 blocks <NUM>, or the 8x8 blocks <NUM>, as shown, and may include determining whether to partition into one or more smaller partitions. For example, a 64x64 block may be partitioned into four 32x32 partitions. Three of the four 32x32 partitions may be encoded as 32x32 partitions and the fourth 32x32 partition may be further partitioned into four 16x16 partitions. Three of the four 16x16 partitions may be encoded as 16x16 partitions and the fourth 16x16 partition may be further partitioned into four 8x8 partitions, each of which may be encoded as an 8x8 partition. In some implementations, identifying the partitioning scheme may include using a partitioning decision tree.

An optimal coding mode may be identified from multiple candidate coding modes, which provides flexibility in handling video signals with various statistical properties and may improve the compression efficiency. For example, a video coder may evaluate each candidate coding mode to identify the optimal coding mode. The optimal coding mode is often the coding mode that minimizes an error metric, such as a rate-distortion cost, for the current block. The complexity of searching the candidate coding modes may be reduced by limiting the set of available candidate coding modes based on similarities between the current block and a corresponding prediction block. Further reductions in complexity may be achieved by performing a directed refinement mode search. For example, metrics may be generated for a limited set of candidate block sizes, such as 16x16, 8x8, and 4x4, the error metric associated with each block size may be in descending order, and additional candidate block sizes, such as 4x8 and 8x4 block sizes, may be evaluated,.

In some implementations, alternating block constrained decision mode coding may be used, which alternates between an unconstrained decision mode, wherein the set of candidate coding modes may be fully searched, and a constrained mode, wherein the set of candidate coding modes to be searched may be limited. The alternating may be spatial, temporal, or both spatial and temporal. Spatial alternating includes alternating between constrained and unconstrained modes among immediately adjacent, neighboring, blocks and may be vertical, horizontal, or both. This may be represented as a checkerboard, or chessboard, pattern. Temporal alternating may alternate between constrained and unconstrained modes among immediately adjacent frames.

<FIG> is a diagram of an example of a quantized transform coefficient matrix <NUM> including a 4x4 block of quantized transform coefficient values in accordance with this disclosure. For example, an element of an encoder, such as quantization unit <NUM> of encoder <NUM> shown in <FIG>, may generate quantized transform coefficient matrix <NUM>. Although a 4x4 block is shown for simplicity, any size block may be used. For example, a 64x64 block, a 64x32 block, a 32x64 block, a 32x32 block, a 32x16 block, a 16x32 block, a 16x16 block, a 16x8 block, an 8x16 block, an 8x8 block, an 8x4 block, or a 4x8 block, may be used.

In <FIG>, the value shown in each location indicates the transform coefficient value for the respective location. For clarity, the location of a transform coefficient for a block may be referred to as the "position," "location," or variations thereof, of the transform coefficient. As used herein, references to "proximity," "spatial proximity," or "distance" between transform coefficients may indicate proximity or distance in the transform coefficient matrix representation of the transform coefficients for a block. Although the transform coefficients are described with relation to a transform coefficient matrix, the transform coefficients may be processed or stored in any data structure. For example, the transform coefficients may be processed or stored in a one dimensional array, such as a vector.

A transform, such a symmetric DCT, tends to group coefficients having large magnitudes in the upper left corner of block <NUM> as shown. In some implementations, a transform can distribute larger magnitude coefficients in a different pattern. For example a one-dimensional asymmetric discrete sine transform (ADST) combined with a one-dimensional DCT tends to group large magnitude coefficients along one edge of the block, such as the top edge or the left edge.

The matrix of quantized transformed coefficients may be processed in a scan order that tends to group the zero value coefficients at the end of the block. Then, consecutive zero value coefficients at the end of a block in scan order may be omitted from the output bitstream without loss of data. Although not explicitly shown, the two-dimensional (2D) transform coefficient matrix may be represented by a one-dimensional vector array.

<FIG> shows diagrams of examples of entropy coding scan orders in accordance with this disclosure. Entropy coding includes encoding the coefficients of a quantized transform coefficient matrix, such as quantized transform coefficient matrix <NUM> shown in <FIG>, in a scan order, such as a horizontal scan order <NUM>, a vertical scan order <NUM>, a diagonal scan order <NUM>, or a zigzag scan order <NUM>. In <FIG>, the values shown in each block represent the order that the corresponding coefficient is entropy coded. Although a 4x4 block is shown for simplicity, any size block may be used. For example, a 64x64 block, a 64x32 block, a 32x64 block, a 32x32 block, a 32x16 block, a 16x32 block, a 16x16 block, a 16x8 block, an 8x16 block, an 8x8 block, an 8x4 block, or a 4x8 block, may be used.

A one-dimensional array, such as a vector, of the transform coefficients may be generated by including each transform coefficient in the vector in scan order. For example, a DC coefficient in the top left corner of the transform coefficient matrix may be the first element of the scan order vector, thus having a transform coefficient matrix location of (<NUM>,<NUM>) and a scan order position of (<NUM>). As used herein, the terms "order," "scan position," "vector position," or variations thereof of a transform coefficient indicate a relative position, or index, of the transform coefficient in the scan order or the scan order vector. Although <FIG> shows examples of sequential scan patterns, the coefficients may be coded using a non-contiguous scan pattern. <FIG> shows a diagram of an example of a portion of a non-contiguous entropy coding scan order in accordance with disclosure. For example, <FIG> may show a portion of a scan order for a 32x32 block.

<FIG> is a flow diagram of contextual entropy encoding in accordance with this disclosure. Contextual entropy coding can be implemented in an encoder, such as encoder <NUM> shown in <FIG>, of a device, such as computing device <NUM> shown in <FIG> or computing and communication devices 100A/100B/100C shown in <FIG>. It may be implemented, as, for example, a computer software program stored in a data storage unit, such as memory <NUM> shown in <FIG>.

Contextual entropy coding may be used to encode a stream of video data having multiple frames, each having multiple blocks. The video data or stream can be received by the computing device in any number of ways, such as by receiving the video data over a network, over a cable, or by reading the video data from a primary memory or other storage device, including a disk drive or removable media such as a CompactFlash (CF) card, Secure Digital (SD) card, or any other device capable of communicating video data. In some implementations, video data can be received from a video camera connected to the computing device operating the encoder.

As shown in <FIG>, contextual entropy coding includes identifying transform coefficients for a current block of a current frame at <NUM>, identifying a current transform coefficient at <NUM>, identifying context coefficients for the current transform coefficient at <NUM>, and entropy coding the current transform coefficient at <NUM>.

Identifying the transform coefficients at <NUM> may include generating, reading, receiving, or otherwise distinguishing a block of transform coefficients, such as block of transform coefficients <NUM> shown in <FIG>, associated with a current block of a current frame. Transform coefficients are numerical values formed by, for example, processing pixels of a block of a frame of a video stream by a unit of an encoder, such as transform unit <NUM> shown in <FIG>. Although referred to as "transform coefficients" or "coefficients" for simplicity, the transform coefficients may be quantized transform coefficients, such as the quantized transform coefficients generated by quantization unit <NUM> shown in <FIG>.

The transform coefficients may then be ordered based on a scan order, such as the zigzag scan order <NUM> shown <FIG>. For example, an ordered one-dimensional array, or vector, of transform coefficients is generated from a two-dimensional matrix of transform coefficients by including coefficients in the vector in scan order.

A current transform coefficient is identified at <NUM>. For example, the transform coefficients may be processed in scan order, and identifying the current transform coefficient includes identifying the next coefficient in scan order. In some implementations, the current transform coefficient may be a zero value transform coefficient. When the current block of transform coefficients does not include a subsequent non-zero value transform coefficient, entropy coding for the current block is complete.

Context coefficients for the current transform coefficient are identified at <NUM>. In some implementations, the probability distribution for entropy coding the current coefficient is adapted based on the context coefficients. The context coefficients may include previously entropy coded coefficients from the current frame that are spatially proximate to the current coefficient. For example, the context coefficients may include previously entropy coded transform coefficients that are spatially proximate to the current coefficient in the current block of transform coefficients, such as the coefficient immediately to the left of the current coefficient, the coefficient immediately above the current coefficient, or the coefficient immediately above and to the left of the current coefficient.

Context coefficients identified for the current coefficient may depend on the spatial location of the current coefficient in the transform coefficient matrix. For example, the current coefficient may be the top-left coefficient in the transform coefficient matrix and identifying context coefficients are omitted. In some implementations, the current coefficient may be in the top row of the transform coefficient matrix, previously entropy coded coefficients above the current coefficient are not be available and previously entropy coded coefficients to the left of the current coefficient are identified as the context coefficients. For example, the current coefficient may be the coefficient in the first row and third column of the transform coefficient matrix, and the context coefficients include the coefficient in the first row and second column and the coefficient in the first row and first column of the transform coefficient matrix. In other implementations, the current coefficient may be in the leftmost column of the transform coefficient matrix, previously entropy coded coefficients to the left of the current coefficient are be available and previously entropy coded coefficients above the current coefficient are identified as the context coefficients. For example, the current coefficient may be the coefficient in the third row and first column of the transform coefficient matrix, and the context coefficients include the coefficient in the second row and first column and the coefficient in the first row and first column of the transform coefficient matrix.

The current transform coefficient is entropy coded at <NUM>, which may include identifying a token, or codeword, for the current coefficient. The entropy coded current transform coefficient may be included in an output bitstream, such as compressed bitstream <NUM> shown in <FIG>. That is, for example, the token for the current coefficient may be included in the output bitstream to represent the current coefficient. Entropy coding the current transform coefficient at <NUM> may also include storing or transmitting the output bitstream. For example, the encoded video bitstream, including the token representing the entropy coded current transform coefficient, may be transmitted as a signal via a network, such as network <NUM> shown in <FIG>, so that a device, such as computing device <NUM> shown in <FIG> or computing and communication devices 100A/100B/100C shown in <FIG>, which may include a decoder, such as decoder <NUM> shown in <FIG>, receives the signal via the network, decodes the encoded video bitstream, and generates a reconstructed frame, or a portion of a reconstructed frame, corresponding to the current frame.

The encoded video bitstream, including the token representing the entropy coded current transform coefficient, may be stored in a memory, such as memory <NUM> shown in <FIG>, of a device, such as computing device <NUM> shown in <FIG> or computing and communication devices 100A/100B/100C shown in <FIG>. The encoded video bitstream may be stored as a stored encoded video, such that the device, or any other device capable of accessing the memory, may retrieve the stored encoded video, such that a decoder may decode the encoded video and generate a reconstructed frame, or a portion of a reconstructed frame, corresponding to the current frame.

Other implementations of the diagram of contextual entropy encoding as shown in <FIG> are available. Additional elements can be added, certain elements can be combined, and/or certain elements can be removed. For example, contextual entropy encoding can include an additional element involving generating entropy coding models.

<FIG> is a flow diagram of contextual entropy decoding in accordance with an implementation of this disclosure. Contextual entropy decoding can be implemented in an decoder, such as decoder <NUM> shown in <FIG>, of a device, such as computing device <NUM> shown in <FIG> or computing and communication devices 100A/100B/100C shown in <FIG>. The decoding may be implemented as, for example, a computer software program stored in a data storage unit, such as memory <NUM> shown in <FIG>.

As shown in <FIG>, contextual entropy decoding includes identifying entropy decoded transform coefficients for a current block of a current frame at <NUM>, identifying a current entropy coded transform coefficient at <NUM>, identifying context coefficients for the current entropy coded transform coefficient at <NUM>, and entropy decoding the current entropy coded transform coefficient at <NUM>.

Although not explicitly shown in <FIG>, contextual entropy decoding may include receiving a signal including an encoded video stream, or a portion of an encoded video stream, via a network, such as network <NUM> shown in <FIG>, or retrieving an encoded video stream, or a portion of an encoded video stream, from a memory, such as memory <NUM> shown in <FIG>. For simplicity, as used herein, receiving may include receiving via a network, retrieving from memory, or otherwise ascertaining the identified information.

Entropy decoded transform coefficients for a current block of a current frame are identified at <NUM> by, for example, identifying a current block of a current frame of a current video stream, and generating the entropy decoded transform coefficients for the current block from the encoded video stream.

The entropy decoded transform coefficients may be identified in a scan order for the current block. For example, the encoded video stream may be received as a one-dimensional array, or vector, of tokens, or codewords, wherein each token represents an encoded transform coefficient of the current block in a scan order. For example, the token corresponding to the transform coefficient in the top-left location of a transform coefficient matrix is the first token received and entropy decoded, and the next token in scan order is the next token received and entropy decoded. Identifying the entropy decoded transform coefficients can include identifying a location for each entropy decoded transform coefficient in a transform coefficient matrix for the current block based on the order the entropy decoded transform coefficient is received and the scan order.

A current entropy coded transform coefficient may be identified at <NUM>. More specifically, a current token, or codeword, representing the current entropy coded transform coefficient may be identified in the received encoded bitstream. Identifying the current entropy coded transform coefficient at <NUM> may thus include identifying a location of the transform coefficient represented by the current token in the transform coefficient matrix for the current block. For example, the current token may be received as part of a one dimensional sequence, or vector array, and a location of the corresponding transform coefficient in the transform coefficient matrix for the current block is identified based on the scan order for the current block. For simplicity, the transform coefficient represented by the current token is referred to as the current transform coefficient or the current coefficient.

Context coefficients for entropy decoding the current transform coefficient from the current token are identified at <NUM>. For example, the current token may be entropy decoded based on a probability distribution that is adapted based on the context coefficients.

The context coefficients may include previously entropy decoded coefficients from the current frame that are spatially proximate to the location of the current transform coefficient in the transform coefficient matrix. For example, the context coefficients include previously entropy decoded transform coefficients that are spatially proximate to the location of the current coefficient in the current block of transform coefficients, such as the coefficient immediately to the left of the location of the current coefficient, the coefficient immediately above the location of the current coefficient, or the coefficient immediately above and to the left of the location of the current coefficient.

The context coefficients for entropy decoding the current coefficient may be identified based on the spatial location of the current coefficient in the transform coefficient matrix. For example, the current coefficient may be the top-left coefficient in the transform coefficient matrix and identifying context coefficients is omitted. The current coefficient may be in the top row of the transform coefficient matrix, previously entropy decoded coefficients above the current coefficient are not be available and previously entropy decoded coefficients to the left of the current coefficient are identified as the context coefficients. For example, the current coefficient may be the coefficient in the first row and third column of the transform coefficient matrix, and the context coefficients include the entropy decoded coefficient in the first row and second column and the entropy decoded coefficient in the first row and first column of the transform coefficient matrix. The current coefficient may be in the leftmost column of the transform coefficient matrix, previously entropy decoded coefficients to the left of the current coefficient are not available and previously entropy decoded coefficients above the current coefficient are identified as the context coefficients. For example, the current coefficient may be the coefficient in the third row and first column of the transform coefficient matrix, and the context coefficients include the entropy decoded coefficient in the second row and first column and the entropy decoded coefficient in the first row and first column of the transform coefficient matrix.

The current transform coefficient is entropy decoded at <NUM> by identifying a value of the current transform coefficient. The value is the value of the current transform coefficient in the transform coefficient matrix for the current block at the location identified for the current transform coefficient at <NUM>.

Although not shown in <FIG>, contextual entropy decoding may be performed for each coefficient in the transform coefficient matrix for the current block, and an output video stream, such as the output video stream <NUM> shown in <FIG>, or a portion of the output video stream, may be generated based on the transform coefficient matrix for the current block as shown in <FIG>. For example, the transform coefficient matrix for the current block may be output to a dequantization unit, such as dequantization unit <NUM> shown in <FIG>, or may be stored in a memory, such as memory <NUM> shown in <FIG>. The decoded video stream may be output to a presentation unit, such as user interface <NUM> shown in <FIG>, for display.

Other implementations of contextual entropy decoding than that shown in <FIG> are available. Additional elements of contextual entropy decoding can be added, certain elements can be combined, and/or certain elements can be removed. For example, contextual entropy decoding can include an additional element involving generating entropy coding models.

Contextual entropy decoding may include storing each decoded coefficient for a block in a decoder coefficient register, which may be stored in a data storage unit, such as memory <NUM> shown in <FIG>. In this case, identifying the context coefficients at <NUM> includes reading the context coefficients from the decoder coefficient register.

The size of the context coefficient register may be a function of the size of the coefficient matrix used for coding. For example, the coefficient matrix may be a NxM matrix, such as a 32x32 matrix, encoded using a non-contiguous coding order, such as the coding order partially shown in <FIG>, and the context coefficient register may include N*M coefficients, such as <NUM> (<NUM>*<NUM>=<NUM>) coefficients. Each coefficient may be stored using B bits, such as <NUM> bits, and the size of the context coefficient register may be B*N*M bits, such as <NUM> bits (<NUM>*3bits).

<FIG> is a diagram of a portion <NUM> of a transform coefficient scan pattern for encoding and decoding using efficient context handling in arithmetic coding in accordance with this disclosure. Decoding a current coefficient may be based on a reduced size context coefficient register. For example, efficient context handling in arithmetic coding may include decoding a current coefficient for a 32x32 matrix encoded using the non-contiguous coding order, such as the non-contiguous coding order partially shown in <FIG> or at <NUM> in <FIG>, based on a context coefficient register including <NUM> coefficients.

A current coefficient <NUM> at scan order location <NUM> may be decoded using the coefficient to the left of the current coefficient, here coefficient <NUM> at scan order location <NUM>, the coefficient to above the current coefficient, here coefficient <NUM> at scan order location <NUM>, or a combination thereof. In <FIG>, the current scan order location, corresponding to the current encoded coefficient, is shown with a bold boarder, scan order locations corresponding to decoded coefficients are shown with a white background, and scan order locations corresponding to encoded coefficients are shown with a lined background.

An example of a portion 1250A of the context coefficient register is shown, including the coefficients at scan order locations <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM>. The portion of the context coefficient register after a shift operation is shown at 1250B, and includes the coefficients at scan order locations <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, <NUM>, and <NUM>.

<FIG> is a flow diagram of contextual entropy decoding using efficient context handling in arithmetic coding in accordance with this disclosure. Contextual entropy decoding using efficient context handling in arithmetic coding can be implemented in an decoder, such as decoder <NUM> shown in <FIG>, of a device, such as computing device <NUM> shown in <FIG> or computing and communication devices 100A/100B/100C shown in <FIG>. The decoding can be implemented as, for example, a computer software program stored in a data storage unit, such as memory <NUM> shown in <FIG>.

As shown in <FIG>, contextual entropy decoding using efficient context handling in arithmetic coding includes identifying a scan order at <NUM>, identifying a distance table at <NUM>, identifying entropy decoded transform coefficients for a current block of a current frame at <NUM>, identifying a current entropy coded transform coefficient at <NUM>, identifying context coefficients for the current entropy coded transform coefficient at <NUM>, and entropy decoding the current entropy coded transform coefficient at <NUM>.

Although not explicitly shown in <FIG>, contextual entropy decoding may include receiving a signal including an encoded video stream, or a portion of an encoded video stream, via a network, such as network <NUM> shown in <FIG>, or retrieving an encoded video stream, or a portion of an encoded video stream, from a memory, such as such as memory <NUM> shown in <FIG>. For simplicity, as used herein, receiving may include receiving via a network, retrieving from memory, or otherwise ascertaining the identified information.

The scan order for the current block of the current frame is identified at <NUM>. For example, the current block may be a 32x32 block and the scan order may be a 32x32 scan order, such as the scan order partially shown in <FIG> and <FIG>.

A distance table is identified at <NUM>. The distance table may be a defined distance table, such as a previously generated distance table. Alternatively, identifying the distance table may include generating the distance table. In some implementations, generating the distance table may include determining scan order distances between a target coefficient and context coefficients for the context coefficient. For example, and referring to <FIG>, the target coefficient may be the coefficient at scan order position <NUM>, the left context coefficient is the coefficient at scan order position <NUM>, the above context coefficient is the coefficient at scan order position <NUM>, the scan order distance between the target coefficient at <NUM> and the left context coefficient at <NUM> is <NUM>, and the scan order distance between the target coefficient at <NUM> and the above context coefficient at <NUM> is <NUM>. Scan order distance values may be identified for each coefficient in the current block, which may exclude the coefficient in scan order location zero (<NUM>).

Although not shown separately in <FIG>, contextual entropy decoding using efficient context handling in arithmetic coding may include determining a size for a decoder coefficient register based on the distance table identified at <NUM>. The size of the decoder coefficient register may be one less than the maximal distance value identified at <NUM> for a block based on the scan order in some implementations.

Entropy decoded transform coefficients for a current block of a current frame is identified at <NUM>. For example, identifying the entropy decoded transform coefficients at <NUM> includes identifying a current block of a current frame of a current video stream, and generating the entropy decoded transform coefficients for the current block from the encoded video stream.

Thereafter, the entropy decoded transform coefficients are identified based on the scan order identified for the current block at <NUM>. For example, the encoded video stream may be received as a one dimensional array, or vector, of tokens, or codewords, wherein each token represents an encoded transform coefficient of the current block in a scan order. For example, the token corresponding to the transform coefficient in the top-left location of a transform coefficient matrix may be the first token received and entropy decoded, and the next token in scan order is the next token received and entropy decoded. In some implementations, identifying the entropy decoded transform coefficients may include identifying a location for each entropy decoded transform coefficient in a transform coefficient matrix for the current block based on the order the entropy decoded transform coefficient is received and the scan order.

One or more of the entropy decoded transform coefficients may be stored in a decoder coefficient register, such as decoder coefficient register <NUM> shown in <FIG>. Storing the entropy decoded transform coefficients in the decoder coefficient register may include decoding a transform coefficient and performing a shift operation to store the entropy decoded transform coefficient in the decoder coefficient register. When the decoder coefficient register is full, an entropy decoded transform coefficient, such as the most distantly decoded entropy decoded transform coefficient, may be removed from the decoder coefficient register.

A current entropy coded transform coefficient is identified at <NUM>. For example, a current token, or codeword, representing the current entropy coded transform coefficient may be identified in the received encoded bitstream. In some implementations, identifying the current entropy coded transform coefficient at <NUM> includes identifying a location of the transform coefficient represented by the current token in the transform coefficient matrix for the current block. In an example, the current token is received as part of a one-dimensional sequence, or vector array, and a location of the corresponding transform coefficient in the transform coefficient matrix for the current block is identified based on the scan order for the current block. For simplicity, the transform coefficient represented by the current token may be referred to as the current transform coefficient or the current coefficient.

Context coefficients for entropy decoding the current transform coefficient from the current token are identified at <NUM>. The current token may be entropy decoded based on a probability distribution that is adapted based on the context coefficients.

The context coefficients for entropy decoding the current coefficient may identified based on the spatial location of the current coefficient in the transform coefficient matrix. For example, the current coefficient may be the top-left coefficient in the transform coefficient matrix, and identifying context coefficients is omitted. The current coefficient may be in the top row of the transform coefficient matrix, previously entropy decoded coefficients above the current coefficient are not available and previously entropy decoded coefficients to the left of the current coefficient are identified as the context coefficients. For example, the current coefficient may be the coefficient in the first row and third column of the transform coefficient matrix, and the context coefficients include the entropy decoded coefficient in the first row and second column and the entropy decoded coefficient in the first row and first column of the transform coefficient matrix. The current coefficient may be in the leftmost column of the transform coefficient matrix, previously entropy decoded coefficients to the left of the current coefficient are not available and previously entropy decoded coefficients above the current coefficient are identified as the context coefficients. For example, the current coefficient may be the coefficient in the third row and first column of the transform coefficient matrix and the context coefficients include the entropy decoded coefficient in the second row and first column and the entropy decoded coefficient in the first row and first column of the transform coefficient matrix.

The context coefficients may be identified from the decoder coefficient register based on the distance values identified at <NUM>. For example, referring to <FIG>, the current coefficient may be coefficient <NUM> at scan order location <NUM>, the distance table identified at <NUM> may indicate a context coefficient distance for the left context coefficient of five (<NUM>), and the value of the coefficient corresponding to scan order position six (<NUM>) may be identified at the fifth decoder coefficient register position, which has an index of four (<NUM>) in the zero based decoder coefficient register 1250A shown in <FIG>. Similarly, the distance table identified at <NUM> may indicate a context coefficient distance for the above context coefficient of four (<NUM>), and the value of the coefficient corresponding to scan order position five (<NUM>) may be identified at the fourth decoder coefficient register position, which has an index of three (<NUM>) in the zero based decoder coefficient register 1250A shown in <FIG>.

The current transform coefficient is entropy decoded at <NUM>. In some implementations, entropy decoding the current transform coefficient at <NUM> includes identifying a value of the current transform coefficient. Entropy decoding the current transform coefficient may also include the value of the current transform coefficient in the transform coefficient matrix for the current block at the location identified for the current transform coefficient at <NUM>.

Entropy decoding the current transform coefficient may include performing a shift operation to store the entropy decoded transform coefficient in the decoder coefficient register. For example, referring to <FIG>, a shift operation may be performed on the decoder coefficient register 1250A to store the coefficient corresponding to scan order position <NUM>, as shown in decoder coefficient register 1250B.

Although not shown in <FIG>, contextual entropy decoding may be performed for each coefficient in the transform coefficient matrix for the current block, and an output video stream, such as output video stream <NUM> shown in <FIG>, or a portion of the output video stream, may be generated based on the transform coefficient matrix for the current block as shown in <FIG>. For example, the transform coefficient matrix for the current block may be output to a dequantization unit, such as dequantization unit <NUM> shown in <FIG>, or may be stored in a memory, such as memory <NUM> shown in <FIG>. In some implementations, the decoded video stream may be output to a presentation unit, such as user interface <NUM> shown in <FIG>, for display.

Other implementations of the diagram of contextual entropy decoding as shown in <FIG> are available. For example, additional elements of contextual entropy decoding can be added, certain elements can be combined, and/or certain elements can be removed. Contextual entropy decoding may include an additional element involving generating entropy coding models in an implementation.

The word "example" is used herein to mean serving as an example, instance, or illustration. Any aspect or design described herein as "example" is not necessarily to be construed as preferred or advantageous over other aspects or designs. Rather, use of the word "example" 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. As used herein, the terms "determine" and "identify", or any variations thereof, includes selecting, ascertaining, computing, looking up, receiving, determining, establishing, obtaining, or otherwise identifying or determining in any manner whatsoever using one or more of the devices shown in <FIG>.

Further, for simplicity of explanation, although the figures and descriptions herein may include sequences or series of steps or stages, elements of the methods disclosed herein can occur in various orders and/or concurrently. Additionally, elements of the methods disclosed herein may occur with other elements not explicitly presented and described herein. Furthermore, not all elements of the methods described herein may be required to implement a method in accordance with the disclosed subject matter.

The implementations of transmitting station 100A and/or receiving station 100B (and the algorithms, methods, instructions, etc. stored thereon and/or executed thereby) can be realized in hardware, software, or any combination thereof. The hardware can include, for example, computers, intellectual property (IP) cores, application-specific integrated circuits (ASICs), programmable logic arrays, optical processors, programmable logic controllers, microcode, microcontrollers, servers, microprocessors, digital signal processors or any other suitable circuit. In the claims, the term "processor" should be understood as encompassing any of the foregoing hardware, either singly or in combination. The terms "signal" and "data" are used interchangeably. Further, portions of transmitting station 100A and receiving station 100B do not necessarily have to be implemented in the same manner.

Further, in one implementation, for example, transmitting station 100A or receiving station 100B can be implemented using a general purpose computer or general purpose /processor with a computer program that, when executed, carries out any of the respective methods, algorithms and/or instructions described herein. In addition or alternatively, for example, a special purpose computer/processor can be utilized which can contain specialized hardware for carrying out any of the methods, algorithms, or instructions described herein.

Transmitting station 100A and receiving station 100B can, for example, be implemented on computers in a real-time video system. Alternatively, transmitting station 100A can be implemented on a server and receiving station 100B can be implemented on a device separate from the server, such as a hand-held communications device. In this instance, transmitting station 100A can encode content using an encoder <NUM> into an encoded video signal and transmit the encoded video signal to the communications device. In turn, the communications device can then decode the encoded video signal using a decoder <NUM>. Alternatively, the communications device can decode content stored locally on the communications device, for example, content that was not transmitted by transmitting station 100A. Other suitable transmitting station 100A and receiving station 100B implementation schemes are available. For example, receiving station 100B can be a generally stationary personal computer rather than a portable communications device and/or a device including an encoder <NUM> may also include a decoder <NUM>.

Further, all or a portion of implementations can take the form of a computer program product accessible from, for example, a tangible computer-usable or computer-readable medium. A computer-usable or computer-readable medium can be any device that can, for example, tangibly contain, store, communicate, or transport the program for use by or in connection with any processor. The medium can be, for example, an electronic, magnetic, optical, electromagnetic, or a semiconductor device. Other suitable mediums are also available.

Claim 1:
An apparatus for decoding a current block in a scan order, wherein the apparatus
identifies a current entropy coded transform coefficient from the current block (<NUM>);
determines, based on the scan order (<NUM>) and using a scan order distance table (<NUM>), a first scan order distance, wherein the first scan order distance is a difference between a first scan order location corresponding to the current entropy coded transform coefficient and a second scan order location corresponding to a first context coefficient, wherein the first context coefficient is spatially proximate to the current entropy coded transform coefficient;
identifies, using the first scan order distance, a first location into a context coefficient register (<NUM>), wherein a size for the context coefficient register is determined based on the scan order distance table;
identifies, at the first location of the context coefficient register, a first context coefficient value (<NUM>);
identifies a probability distribution using at least the first context coefficient value;
entropy decodes the current entropy coded transform coefficient (<NUM>) based on the probability distribution to obtain an entropy decoded current transform coefficient; and
includes the entropy decoded current transform coefficient in an output bitstream.