WO2018179851A1

WO2018179851A1 - Systems and methods for determining a level of quantization

Info

Publication number: WO2018179851A1
Application number: PCT/JP2018/003885
Authority: WO
Inventors: Michael Horowitz; Kiran Mukesh MISRA; Jie Zhao; Christopher Andrew Segall
Original assignee: Sharp Kabushiki Kaisha
Priority date: 2017-03-28
Filing date: 2018-02-06
Publication date: 2018-10-04

Abstract

A method of coding of video data, comprising: for each test candidate in a set of test candidates, generating a respective block of video data; selecting a test candidate based on a respective block of video data and a property of video data; and outputting a reconstructed block of video data corresponding to the selected test candidate.

Description

SYSTEMS AND METHODS FOR DETERMINING A LEVEL OF QUANTIZATION

This disclosure relates to video coding and more particularly to techniques for determining a level of quantization.

Digital video capabilities can be incorporated into a wide range of devices, including digital televisions, laptop or desktop computers, tablet computers, digital recording devices, digital media players, video gaming devices, cellular telephones, including so-called smartphones, medical imaging devices, and the like. Digital video may be coded according to a video coding standard. Video coding standards may incorporate video compression techniques. Examples of video coding standards include ISO/IEC MPEG-4 Visual and ITU-T H.264 (also known as ISO/IEC MPEG-4 AVC) and High-Efficiency Video Coding (HEVC). HEVC is described in High Efficiency Video Coding (HEVC), Rec. ITU-T H.265 April 2015, which is incorporated by reference, and referred to herein as ITU-T H.265. Extensions and improvements for ITU-T H.265 are currently being considered for development of next generation video coding standards. For example, the ITU-T Video Coding Experts Group (VCEG) and ISO/IEC (Moving Picture Experts Group (MPEG) (collectively referred to as the Joint Video Exploration Team (JVET)) are studying the potential need for standardization of future video coding technology with a compression capability that significantly exceeds that of the current HEVC standard. The Joint Exploration Model 3 (JEM 3), Algorithm Description of Joint Exploration Test Model 3 (JEM 3), ISO/IEC JTC1/SC29/WG11 Document: JVET-C1001v3, May 2016, Geneva, CH, which is incorporated by reference herein, describes the coding features that are under coordinated test model study by the JVET as potentially enhancing video coding technology beyond the capabilities of ITU-T H.265. It should be noted that the coding features of JEM 3 are implemented in JEM reference software maintained by the Fraunhofer research organization. Currently, the updated JEM reference software version 3 (JEM 3.0) is available. As used herein, the term JEM is used to collectively refer to algorithms included in JEM 3 and implementations of JEM reference software.

Video compression techniques enable data requirements for storing and transmitting video data to be reduced. Video compression techniques may reduce data requirements by exploiting the inherent redundancies in a video sequence. Video compression techniques may sub-divide a video sequence into successively smaller portions (i.e., groups of frames within a video sequence, a frame within a group of frames, slices within a frame, coding tree units (e.g., macroblocks) within a slice, coding blocks within a coding tree unit, etc.). Intra prediction coding techniques (e.g., intra-picture (spatial)) and inter prediction techniques (i.e., inter-picture (temporal)) may be used to generate difference values between a unit of video data to be coded and a reference unit of video data. The difference values may be referred to as residual data. Residual data may be coded as quantized transform coefficients. Syntax elements may relate residual data and a reference coding unit (e.g., intra-prediction mode indices, motion vectors, and block vectors). Residual data and syntax elements may be entropy coded. Entropy encoded residual data and syntax elements may be included in a compliant bitstream.

In general, this disclosure describes various techniques for coding video data. In particular, this disclosure describes techniques for determining a level of quantization. It should be noted that although techniques of this disclosure are described with respect to ITU-T H.264, ITU-T H.265, and JEM, the techniques of this disclosure are generally applicable to video coding. For example, the coding techniques described herein may be incorporated into video coding systems, (including video coding systems based on future video coding standards) including block structures, intra prediction techniques, inter prediction techniques, transform techniques, filtering techniques, and/or entropy coding techniques other than those included in ITU-T H.265 and JEM. Thus, reference to ITU-T H.264, ITU-T H.265, and/or JEM is for descriptive purposes and should not be construed to limit the scope of the techniques described herein. Further, it should be noted that incorporation by reference of documents herein is for descriptive purposes and should not be construed to limit or create ambiguity with respect to terms used herein. For example, in the case where an incorporated reference provides a different definition of a term than another incorporated reference and/or as the term is used herein, the term should be interpreted in a manner that broadly includes each respective definition and/or in a manner that includes each of the particular definitions in the alternative.

An aspect of the invention is a method of coding of video data, the method comprising: receiving an array of transform coefficient values; for each test candidate in a set of candidates, generating a reconstructed block of video data corresponding to the array of transform coefficients; selecting one of the test candidates based on a respective reconstructed block of video data and a property of video data; and outputting level values corresponding to the selected test candidate.

An aspect of the invention is a method of coding of video data, the method comprising: receiving an array of level values; for each test candidate in a set of test candidates, generating a respective block of video data; selecting a test candidate based on a respective block of video data and a property of video data; and outputting a reconstructed block of video data corresponding to the selected test candidate.

The details of one or more examples are set forth in the accompanying drawings and the description below. Other features, objects, and advantages will be apparent from the description and drawings, and from the claims.

FIG. 1 is a conceptual diagram illustrating an example of a group of pictures coded according to a quad tree binary tree partitioning in accordance with one or more techniques of this disclosure. FIG. 2 is a conceptual diagram illustrating an example of a video component sampling format in accordance with one or more techniques of this disclosure. FIG. 3 is a conceptual diagram illustrating possible coding structures for a block of video data according to one or more techniques of this disclosure. FIG. 4A is a conceptual diagram illustrating an example of coding a block of video data in accordance with one or more techniques of this disclosure. FIG. 4B is a conceptual diagram illustrating an example of coding a block of video data in accordance with one or more techniques of this disclosure. FIG. 5 is a block diagram illustrating an example of a system that may be configured to encode and decode video data according to one or more techniques of this disclosure. FIG. 6 is a block diagram illustrating an example of a video encoder that may be configured to encode video data according to one or more techniques of this disclosure. FIG. 7 is a conceptual diagram illustrating an example of coding a block of video data in accordance with one or more techniques of this disclosure. FIG. 8 is a conceptual diagram illustrating an example of coding a block of video data in accordance with one or more techniques of this disclosure. FIG. 9 is a conceptual diagram illustrating an example of coding a block of video data in accordance with one or more techniques of this disclosure. FIG. 10 is a conceptual diagram illustrating an example of coding a block of video data in accordance with one or more techniques of this disclosure. FIG. 11 is a block diagram illustrating an example of a video decoder that may be configured to decode video data according to one or more techniques of this disclosure. FIG. 12 is a conceptual diagram illustrating an example of coding a block of video data in accordance with one or more techniques of this disclosure. FIG. 13 is a conceptual diagram illustrating an example of coding a block of video data in accordance with one or more techniques of this disclosure.

Video content typically includes video sequences comprised of a series of frames (or pictures). A series of frames may also be referred to as a group of pictures (GOP). Each video frame or picture may include a plurality of slices or tiles, where a slice or tile includes a plurality of video blocks. As used herein, the term video block may generally refer to an area of a picture or may more specifically refer to the largest array of sample values that may be predictively coded, sub-divisions thereof, and/or corresponding structures. Further, the term current video block may refer to an area of a picture being encoded or decoded. A video block may be defined as an array of sample values that may be predictively coded. It should be noted that in some cases pixel values may be described as including sample values for respective components of video data, which may also be referred to as color components, (e.g., luma (Y) and chroma (Cb and Cr) components or red, green, and blue components). It should be noted that in some cases, the terms pixel values and sample values are used interchangeably. Video blocks may be ordered within a picture according to a scan pattern (e.g., a raster scan). A video encoder may perform predictive encoding on video blocks and sub-divisions thereof. Video blocks and sub-divisions thereof may be referred to as nodes.

ITU-T H.264 specifies a macroblock including 16x16 luma samples. That is, in ITU-T H.264, a picture is segmented into macroblocks. ITU-T H.265 specifies an analogous Coding Tree Unit (CTU) structure. In ITU-T H.265, pictures are segmented into CTUs. In ITU-T H.265, for a picture, a CTU size may be set as including 16x16, 32x32, or 64x64 luma samples. In ITU-T H.265, a CTU is composed of respective Coding Tree Blocks (CTB) for each component of video data (e.g., luma (Y) and chroma (Cb and Cr). Further, in ITU-T H.265, a CTU may be partitioned according to a quadtree (QT) partitioning structure, which results in the CTBs of the CTU being partitioned into Coding Blocks (CB). That is, in ITU-T H.265, a CTU may be partitioned into quadtree leaf nodes. According to ITU-T H.265, one luma CB together with two corresponding chroma CBs and associated syntax elements are referred to as a coding unit (CU). In ITU-T H.265, a minimum allowed size of a CB may be signaled. In ITU-T H.265, the smallest minimum allowed size of a luma CB is 8x8 luma samples. In ITU-T H.265, the decision to code a picture area using intra prediction or inter prediction is made at the CU level.

In ITU-T H.265, a CU is associated with a prediction unit (PU) structure having its root at the CU. In ITU-T H.265, PU structures allow luma and chroma CBs to be split for purposes of generating corresponding reference samples. That is, in ITU-T H.265, luma and chroma CBs may be split into respect luma and chroma prediction blocks (PBs), where a PB includes a block of sample values for which the same prediction is applied. In ITU-T H.265, a CB may be partitioned into 1, 2, or 4 PBs. ITU-T H.265 supports PB sizes from 64x64 samples down to 4x4 samples. In ITU-T H.265, square PBs are supported for intra prediction, where a CB may form the PB or the CB may be split into four square PBs (i.e., intra prediction PB sizes type include MxM or M/2xM/2, where M is the height and width of the square CB). In ITU-T H.265, in addition to the square PBs, rectangular PBs are supported for inter prediction, where a CB may by halved vertically or horizontally to form PBs (i.e., inter prediction PB types include MxM, M/2xM/2, M/2xM, or MxM/2). Further, it should be noted that in ITU-T H.265, for inter prediction, four asymmetric PB partitions are supported, where the CB is partitioned to into two PBs at one quarter of the height (at the top or the bottom) or width (at the left or the right) of the CB (i.e., asymmetric partitions include M/4xM left, M/4xM right, MxM/4 top, and MxM/4 bottom). Intra prediction data (e.g., intra prediction mode syntax elements) or inter prediction data (e.g., motion data syntax elements) corresponding to a PB is used to produce reference and/or predicted sample values for the PB.

JEM specifies a CTU having a maximum size of 256x256 luma samples. JEM specifies a quadtree plus binary tree (QTBT) block structure. In JEM, the QTBT structure enables quadtree leaf nodes to be further partitioned by a binary tree (BT) structure. That is, in JEM, the binary tree structure enables quadtree leaf nodes to be recursively divided vertically or horizontally. FIG. 1 illustrates an example of a CTU (e.g., a CTU having a size of 256x256 luma samples) being partitioned into quadtree leaf nodes and quadtree leaf nodes being further partitioned according to a binary tree. That is, in FIG. 1 dashed lines indicate additional binary tree partitions in a quadtree. Thus, the binary tree structure in JEM enables square and rectangular leaf nodes, where each leaf node includes a CB. As illustrated in FIG. 1, a picture included in a GOP may include slices, where each slice includes a sequence of CTUs and each CTU may be partitioned according to a QTBT structure. FIG. 1 illustrates an example of QTBT partitioning for one CTU included in a slice.

In JEM, a QTBT is signaled by signaling QT split flag and BT split mode syntax elements. Further, in JEM, luma and chroma components may have separate QTBT partitions. That is, in JEM, luma and chroma components may be partitioned independently by signaling respective QTBTs. Currently, in JEM independent QTBT structures are enabled for slices using intra prediction techniques. In JEM, CBs are used for prediction without any further partitioning. That is, in JEM, a CB may be a block of sample values on which the same prediction is applied. Thus, a JEM QTBT leaf node may be analogous a PB in ITU-T H.265.

A video sampling format, which may also be referred to as a chroma format, may define the number of chroma samples included in a CU with respect to the number of luma samples included in a CU. For example, for the 4:2:0 sampling format, the sampling rate for the luma component is twice that of the chroma components for both the horizontal and vertical directions. As a result, for a CU formatted according to the 4:2:0 format, the width and height of an array of samples for the luma component are twice that of each array of samples for the chroma components. FIG. 2 is a conceptual diagram illustrating an example of a coding unit formatted according to a 4:2:0 sample format. FIG. 2 illustrates the relative position of chroma samples with respect to luma samples within a CU. As described above, a CU is typically defined according to the number of horizontal and vertical luma samples. Thus, as illustrated in FIG. 2, a 16x16 CU formatted according to the 4:2:0 sample format includes 16x16 samples of luma components and 8x8 samples for each chroma component. Further, in the example illustrated in FIG. 2, the relative position of chroma samples with respect to luma samples for video blocks neighboring the 16x16 CU are illustrated. For a CU formatted according to the 4:2:2 format, the width of an array of samples for the luma component is twice that of the width of an array of samples for each chroma component, but the height of the array of samples for the luma component is equal to the height of an array of samples for each chroma component. Further, for a CU formatted according to the 4:4:4 format, an array of samples for the luma component has the same width and height as an array of samples for each chroma component.

As described above, intra prediction data or inter prediction data is used to produce reference sample values for a block of sample values. The difference between sample values included in a current PB, or another type of picture area structure, and associated reference samples (e.g., those generated using a prediction) may be referred to as residual data. As described above, intra prediction data or inter prediction data may associate an area of a picture (e.g., a PB or a CB) with corresponding reference samples. For intra prediction coding, an intra prediction mode may specify the location of reference samples within a picture. In ITU-T H.265, defined possible intra prediction modes include a planar (i.e., surface fitting) prediction mode (predMode: 0), a DC (i.e., flat overall averaging) prediction mode (predMode: 1), and 33 angular prediction modes (predMode: 2-34). In JEM, defined possible intra-prediction modes include a planar prediction mode (predMode: 0), a DC prediction mode (predMode: 1), and 65 angular prediction modes (predMode: 2-66). It should be noted that planar and DC prediction modes may be referred to as non-directional prediction modes and that angular prediction modes may be referred to as directional prediction modes. It should be noted that the techniques described herein may be generally applicable regardless of the number of defined possible prediction modes.

For inter prediction coding, a motion vector (MV) identifies reference samples in a picture other than the picture of a video block to be coded and thereby exploits temporal redundancy in video. For example, a current video block may be predicted from reference block(s) located in previously coded frame(s) and a motion vector may be used to indicate the location of the reference block. A motion vector and associated data may describe, for example, a horizontal component of the motion vector, a vertical component of the motion vector, a resolution for the motion vector (e.g., one-quarter pixel precision, one-half pixel precision, one-pixel precision, two-pixel precision, four-pixel precision), a prediction direction and/or a reference picture index value. Further, a coding standard, such as, for example ITU-T H.265, may support motion vector prediction. Motion vector prediction enables a motion vector to be specified using motion vectors of neighboring blocks. Examples of motion vector prediction include advanced motion vector prediction (AMVP), temporal motion vector prediction (TMVP), so-called “merge” mode, and “skip” and “direct” motion inference. Further, JEM supports advanced temporal motion vector prediction (ATMVP) and Spatial-temporal motion vector prediction (STMVP).

Residual data may include respective arrays of difference values corresponding to each component of video data. Residual data may be in the pixel domain. A transform, such as, a discrete cosine transform (DCT), a discrete sine transform (DST), an integer transform, a wavelet transform, or a conceptually similar transform, may be applied to an array of difference values to generate transform coefficients. It should be noted that in ITU-T H.265, a CU is associated with a transform unit (TU) structure having its root at the CU level. That is, in ITU-T H.265, an array of difference values may be sub-divided for purposes of generating transform coefficients (e.g., four 8x8 transforms may be applied to a 16x16 array of residual values). For each component of video data, such sub-divisions of difference values may be referred to as Transform Blocks (TBs). It should be noted that in ITU-T H.265, TBs are not necessarily aligned with PBs. FIG. 3 illustrates examples of alternative PB and TB combinations that may be used for coding a particular CB.

It should be noted that in JEM, residual values corresponding to a CB are used to generate transform coefficients without further partitioning. That is, in JEM a QTBT leaf node may be analogous to both a PB and a TB in ITU-T H.265. It should be noted that in JEM, a core transform and a subsequent secondary transforms may be applied (in the video encoder) to generate transform coefficients. For a video decoder, the order of transforms is reversed. Further, in JEM, whether a secondary transform is applied to generate transform coefficients may be dependent on a prediction mode.

A quantization process may be performed on transform coefficients. Quantization approximates transform coefficients by amplitudes restricted to a set of specified values. Quantization may be used in order to vary the amount of data required to represent a group of transform coefficients. Quantization may be realized through division of transform coefficients by a quantization scaling factor and any associated rounding functions (e.g., rounding to the nearest integer). Quantized transform coefficients may be referred to as coefficient level values. Inverse quantization (or “dequantization”) may include multiplication of coefficient level values by the quantization scaling factor. It should be noted that as used herein the term quantization process in some instances may refer to division by a scaling factor to generate level values and multiplication by a scaling factor to recover transform coefficients in some instances. That is, a quantization process may refer to quantization in some cases and inverse quantization in some cases. Further, it should be noted that although in the examples below quantization processes are described with respect to arithmetic operations associated with decimal notation, such descriptions are for illustrative purposes and should not be construed as limiting. For example, the techniques described herein may be implemented in a device using binary operations and the like. For example, multiplication and division operations described herein may be implemented using bit shifting operations and the like.

FIGS. 4A-4B are conceptual diagrams illustrating examples of coding a block of video data. As illustrated in FIG. 4A, a current block of video data (e.g., a CB corresponding to a video component) is encoded by generating a residual by subtracting a set of prediction values from the current block of video data, performing a transformation on the residual, and quantizing the transform coefficients to generate level values. As illustrated in FIG. 4B, the current block of video data is decoded by performing inverse quantization on level values, performing an inverse transform, and adding a set of prediction values to the resulting residual. It should be noted that in the examples in FIGS. 4A-4B, the sample values of the reconstructed block differs from the sample values of the current video block that is encoded. In this manner, coding may be said to be lossy. However, the difference in sample values may be considered acceptable to a viewer of the reconstructed video. Further, as illustrated in FIGS. 4A-4B, scaling is performed using an array of scaling factors.

In ITU-T H.265, an array of scaling factors is generated by selecting a scaling matrix and multiplying each entry in the scaling matrix by a quantization scaling factor. In ITU-T H.265, a scaling matrix is selected based on a prediction mode and a color component, where scaling matrices of the following sizes are defined: 4x4, 8x8, 16x16, and 32x32. It should be noted that in some examples, a scaling matrix may provide the same value for each entry (i.e., all coefficients are scaled according to a single value). In ITU-T H.265, the value of a quantization scaling factor, may be determined by a quantization parameter, QP. In ITU-T H.265, the QP can take 52 values from 0 to 51 and a change of 1 for QP generally corresponds to a change in the value of the quantization scaling factor by approximately 12%. Further, in ITU-T H.265, a QP value for a set of transform coefficients may be derived using a predictive quantization parameter value (which may be referred to as a predictive QP value or a QP predictive value) and an optionally signaled quantization parameter delta value (which may be referred to as a QP delta value or a delta QP value). In ITU-T H.265, a quantization parameter may be updated for each CU and a quantization parameter may be derived for each of luma (Y) and chroma (Cb and Cr) components.

In ITU-T H.265, for a current CU, a predictive QP value is inherited for the CU (i.e., a QP signaled at the slice level or a QP from a previous CU) and a delta QP value may be optionally signaled for each TU within the CU. For the luma component, the QP for each luma TB is the sum of the predictive QP value and any signaled delta QP value. In ITU-T H.265, a quantization group size is used to determine if a delta QP can be signaled for a particular TU. For example, a video encoder may select a CTU size of 64x64 and a quantization group size of 32x32. In this case, if the CTU is partitioned (using the quadtree structure provided in ITU-T H.265) into 32x32 TUs, then a delta QP may be signaled for each TU. However, if the 64x64 CTU is partitioned into 8x8 TUs, then a delta QP is only sent for the first 8x8 TU in each 32x32 region. Further, in ITU-T H.265, for the chroma components of the current CU, the chroma QP is a function of the QP determined for the luma component and chroma QP offsets signaled in a slice header and/or chroma QP offsets signaled a picture parameter set (PPS). It should be noted that in ITU-T H.265, the TU structure aligns TBs for each luma and chroma component. That is, in ITU-T H.265, a TB for a component (e.g., a chroma component) directly corresponds to a TB of another component. In an example, the size of a quantization group corresponds to the number of samples in the quantization group.

The dequantization process defined in ITU-T H.265 for each entry in an x by y array may be summarized as follows:
d[x][y] =
((TransCoeffLevel[x][y] * m[x][y] * levelScale[qP%6] << (qP/6)) + (1 << (bdShift-1))) >> bdShift
where
d[x][y] is a resulting transform coefficient;
TransCoeffLevel[x][y] is a coefficient level value;
m[x][y] is a scaling matrix;
levelScale[k] = {40, 45, 51, 57, 64, 72} with k=0..5;
qP is the quantization parameter;
bdShift = BitDepth+ Log2 (nTbS) + 10, where BitDepth is the bit depth of the corresponding component;
Log2( x ) the base-2 logarithm of x;
nTbS specifies the size of the corresponding transform block;
x>>y is an arithmetic right shift of a two’s complement integer representation of x by y binary digits;
x<<y is an arithmetic left shift of a two’s complement integer representation of x by y binary digits; and
x % y is x modulus y.

It should be noted that the transform coefficient at d[0][0] is the DC transform coefficient and the other transform coefficients in the array are the AC transform coefficients.

As described above, quantization may be used in order to vary the amount of data required to represent a group of transform coefficients. For example, a quantization parameter value may be used to generate zero values for a number of transform coefficients in an array. It typically requires less data to represent an array of level values including fewer non-zero level values in a bitstream compared to an array of level values including more non-zero level values. It should be noted that in some cases, non-zero level values may be referred to as significant level values. However, as the level of quantization increases (e.g., transform coefficients are divided by a larger value), the amount of distortion may be increased (e.g., reconstructed video data may appear more “blocky” to a user). Typically, the amount of data required to code video data is expressed as a bit-rate and, as such, the tradeoff between the amount of data required to code video data and the amount of distortion may be referred to as a rate-distortion. Rate control (RC) algorithms may refer to algorithms that code video data according to a specified bit-rate. For example, a rate control algorithm may seek to minimize distortion for a maximum allowable bit-rate (e.g., 5 Megabits per Second (Mb/s)).

RC algorithms performed by a video encoder frequently use the statistical variance of a residual to select a QP value. In some cases, an algorithm may provide that it may be acceptable to quantize a residual having a relatively lower variance using a relatively higher QP. In this manner, conventional RC algorithms implemented in a video encoder may be said to modulate a signaled QP value based on the statistical variance of a residual. As described above, in ITU-T H.265, for a current CU, a predictive QP value is inherited for the CU and a delta QP value may be optionally signaled for each TU within the CU. Thus, in ITU-T H.265, modulation of a signaled QP value is achieved by sending delta QP values which update a predictive QP value. Modulating a level of quantization by signaling delta QP values may be less than ideal.

Referring again to FIG. 4A, quantized transform coefficients are coded into a bitstream. Quantized transform coefficients and syntax elements (e.g., syntax elements indicating a coding structure for a video block) may be entropy coded according to an entropy coding technique. Examples of entropy coding techniques include content adaptive variable length coding (CAVLC), context adaptive binary arithmetic coding (CABAC), probability interval partitioning entropy coding (PIPE), and the like. Entropy encoded quantized transform coefficients and corresponding entropy encoded syntax elements may form a compliant bitstream that can be used to reproduce video data at a video decoder. An entropy coding process may include performing a binarization on syntax elements. Binarization refers to the process of converting a value of a syntax value into a series of one or more bits. These bits may be referred to as “bins.” Binarization is a lossless process and may include one or a combination of the following coding techniques: fixed length coding, unary coding, truncated unary coding, truncated Rice coding, Golomb coding, k-th order exponential Golomb coding, and Golomb-Rice coding. For example, binarization may include representing the integer value of 5 for a syntax element as 00000101 using an 8-bit fixed length binarization technique or representing the integer value of 5 as 11110 using a unary coding binarization technique. As used herein each of the terms fixed length coding, unary coding, truncated unary coding, truncated Rice coding, Golomb coding, k-th order exponential Golomb coding, and Golomb-Rice coding may refer to general implementations of these techniques and/or more specific implementations of these coding techniques. For example, a Golomb-Rice coding implementation may be specifically defined according to a video coding standard, for example, ITU-T H.265. An entropy coding process further includes coding bin values using lossless data compression algorithms. In the example of a CABAC, for a particular bin, a context model may be selected from a set of available context models associated with the bin. In some examples, a context model may be selected based on a previous bin and/or values of previous syntax elements. A context model may identify the probability of a bin having a particular value. For instance, a context model may indicate a 0.7 probability of coding a 0-valued bin and a 0.3 probability of coding a 1-valued bin. It should be noted that in some cases the probability of coding a 0-valued bin and probability of coding a 1-valued bin may not sum to 1. After selecting an available context model, a CABAC entropy encoder may arithmetically code a bin based on the identified context model. The context model may be updated based on the value of a coded bin. The context model may be updated based on an associated variable stored with the context, e.g., adaptation window size, number of bins coded using the context. It should be noted, that according to ITU-T H.265, a CABAC entropy encoder may be implemented, such that some syntax elements may be entropy encoded using arithmetic encoding without the usage of an explicitly assigned context model, such coding may be referred to as bypass coding.

FIG. 5 is a block diagram illustrating an example of a system that may be configured to code (i.e., encode and/or decode) video data according to one or more techniques of this disclosure. System 100 represents an example of a system that may perform video coding using one or more of the techniques for determining a level of quantization. As illustrated in FIG. 5, system 100 includes source device 102, communications medium 110, and destination device 120. In the example illustrated in FIG. 5, source device 102 may include any device configured to encode video data and transmit encoded video data to communications medium 110. Destination device 120 may include any device configured to receive encoded video data via communications medium 110 and to decode encoded video data. Source device 102 and/or destination device 120 may include computing devices equipped for wired and/or wireless communications and may include set top boxes, digital video recorders, televisions, desktop, laptop, or tablet computers, gaming consoles, mobile devices, including, for example, “smart” phones, cellular telephones, personal gaming devices, and medical imagining devices.

Communications medium 110 may include any combination of wireless and wired communication media, and/or storage devices. Communications medium 110 may include coaxial cables, fiber optic cables, twisted pair cables, wireless transmitters and receivers, routers, switches, repeaters, base stations, or any other equipment that may be useful to facilitate communications between various devices and sites. Communications medium 110 may include one or more networks. For example, communications medium 110 may include a network configured to enable access to the World Wide Web, for example, the Internet. A network may operate according to a combination of one or more telecommunication protocols. Telecommunications protocols may include proprietary aspects and/or may include standardized telecommunication protocols. Examples of standardized telecommunications protocols include Digital Video Broadcasting (DVB) standards, Advanced Television Systems Committee (ATSC) standards, Integrated Services Digital Broadcasting (ISDB) standards, Data Over Cable Service Interface Specification (DOCSIS) standards, Global System Mobile Communications (GSM) standards, code division multiple access (CDMA) standards, 3rd Generation Partnership Project (3GPP) standards, European Telecommunications Standards Institute (ETSI) standards, Internet Protocol (IP) standards, Wireless Application Protocol (WAP) standards, and Institute of Electrical and Electronics Engineers (IEEE) standards.

Storage devices may include any type of device or storage medium capable of storing data. A storage medium may include a tangible or non-transitory computer-readable media. A computer readable medium may include optical discs, flash memory, magnetic memory, or any other suitable digital storage media. In some examples, a memory device or portions thereof may be described as non-volatile memory and in other examples portions of memory devices may be described as volatile memory. Examples of volatile memories may include random access memories (RAM), dynamic random access memories (DRAM), and static random access memories (SRAM). Examples of non-volatile memories may include magnetic hard discs, optical discs, floppy discs, flash memories, or forms of electrically programmable memories (EPROM) or electrically erasable and programmable (EEPROM) memories. Storage device(s) may include memory cards (e.g., a Secure Digital (SD) memory card), internal/external hard disk drives, and/or internal/external solid state drives. Data may be stored on a storage device according to a defined file format.

Referring again to FIG. 5, source device 102 includes video source 104, video encoder 106, and interface 108. Video source 104 may include any device configured to capture and/or store video data. For example, video source 104 may include a video camera and a storage device operably coupled thereto. Video encoder 106 may include any device configured to receive video data and generate a compliant bitstream representing the video data. A compliant bitstream may refer to a bitstream that a video decoder can receive and reproduce video data therefrom. Aspects of a compliant bitstream may be defined according to a video coding standard. When generating a compliant bitstream video encoder 106 may compress video data. Compression may be lossy (discernible or indiscernible) or lossless. Interface 108 may include any device configured to receive a compliant video bitstream and transmit and/or store the compliant video bitstream to a communications medium. Interface 108 may include a network interface card, such as an Ethernet card, and may include an optical transceiver, a radio frequency transceiver, or any other type of device that can send and/or receive information. Further, interface 108 may include a computer system interface that may enable a compliant video bitstream to be stored on a storage device. For example, interface 108 may include a chipset supporting Peripheral Component Interconnect (PCI) and Peripheral Component Interconnect Express (PCIe) bus protocols, proprietary bus protocols, Universal Serial Bus (USB) protocols, I²C, or any other logical and physical structure that may be used to interconnect peer devices.

Referring again to FIG. 5, destination device 120 includes interface 122, video decoder 124, and display 126. Interface 122 may include any device configured to receive a compliant video bitstream from a communications medium. Interface 108 may include a network interface card, such as an Ethernet card, and may include an optical transceiver, a radio frequency transceiver, or any other type of device that can receive and/or send information. Further, interface 122 may include a computer system interface enabling a compliant video bitstream to be retrieved from a storage device. For example, interface 122 may include a chipset supporting PCI and PCIe bus protocols, proprietary bus protocols, USB protocols, I²C, or any other logical and physical structure that may be used to interconnect peer devices. Video decoder 124 may include any device configured to receive a compliant bitstream and/or acceptable variations thereof and reproduce video data therefrom. Display 126 may include any device configured to display video data. Display 126 may comprise one of a variety of display devices such as a liquid crystal display (LCD), a plasma display, an organic light emitting diode (OLED) display, or another type of display. Display 126 may include a High Definition display or an Ultra High Definition display. It should be noted that although in the example illustrated in FIG. 5, video decoder 124 is described as outputting data to display 126, video decoder 124 may be configured to output video data to various types of devices and/or sub-components thereof. For example, video decoder 124 may be configured to output video data to any communication medium, as described herein.

FIG. 6 is a block diagram illustrating an example of video encoder 200 that may implement the techniques for encoding video data described herein. It should be noted that although example video encoder 200 is illustrated as having distinct functional blocks, such an illustration is for descriptive purposes and does not limit video encoder 200 and/or sub-components thereof to a particular hardware or software architecture. Functions of video encoder 200 may be realized using any combination of hardware, firmware, and/or software implementations. In one example, video encoder 200 may be configured to encode video data according to the techniques described herein. Video encoder 200 may perform intra prediction coding and inter prediction coding of picture areas, and, as such, may be referred to as a hybrid video encoder. In the example illustrated in FIG. 6, video encoder 200 receives source video blocks and outputs a bitstream. In some examples, source video blocks may include areas of picture that has been divided according to a coding structure. For example, source video data may include macroblocks, CTUs, CBs, sub-divisions thereof, and/or another equivalent coding unit. In some examples, video encoder 200 may be configured to perform additional sub-divisions of source video blocks. It should be noted that some techniques described herein may be generally applicable to video coding, regardless of how source video data is partitioned prior to and/or during encoding.

In the example illustrated in FIG. 6, video encoder 200 includes summer 202, transform coefficient generator 204, coefficient quantization unit 206, inverse quantization/transform processing unit 208, summer 210, intra prediction processing unit 212, inter prediction processing unit 214, post filter unit 216, and entropy encoding unit 218. Video encoder 200 may generate residual data by subtracting a predictive video block from a source video block. Summer 202 represents a component configured to perform this subtraction operation. Transform coefficient generator 204 applies a transform, such as a discrete cosine transform (DCT), a discrete sine transform (DST), or a conceptually similar transform, to the residual block or sub-divisions thereof (e.g., four 8 x 8 transforms may be applied to a 16 x 16 array of residual values) to produce a set of transform coefficients. Transform coefficient generator 204 may be configured to perform any and all combinations of the transforms included in the family of discrete trigonometric transforms. As described above, in ITU-T H.265, TBs are restricted to the following sizes 4x4, 8x8, 16x16, and 32x32. In one example, transform coefficient generator 204 may be configured to perform transformations according to arrays having sizes of 4x4, 8x8, 16x16, and 32x32. In one example, transform coefficient generator 204 may be further configured to perform transformations according to arrays having other dimensions. Transform coefficient generator 204 may output transform coefficients to coefficient quantization unit 206.

Coefficient quantization unit 206 may be configured to perform quantization of the transform coefficients. Coefficient quantization unit 206 may be configured to determine quantization parameters and output QP data (e.g., data used to determine a quantization group size and/or delta QP values) that may be used by a video decoder to reconstruct a quantization parameter to perform inverse quantization during video decoding. As described above, in ITU-T H.265, the degree of quantization may be modulated on a CU-by-CU basis by adjusting a quantization parameter using a delta QP value.

It should be noted that in some cases, it may be useful to use one or more additional or alternative techniques to determine a level of quantization that is performed for a current block of video data. In some examples, in addition to, or as an alternative to signaling delta QP values, it may be useful for a video encoder to perform quantization based on properties of video and/or video coding parameters, i.e., video properties. For example, an intra prediction mode used to generate a prediction may be used to adjust the level of quantization indicated by a predictive QP value. It should be noted that adjusting the level of quantization may include adjusting scaling factors corresponding to a QP value and/or scaling transform coefficients prior to performing a quantization process associated with a QP value. In either of these cases, a video decoder may determine a level of quantization (for performing inverse quantization) based on signaled QP values and/or one or more video coding properties. For example, a video decoder may adjust a scaling factor corresponding to a predictive QP value based on one or more video coding properties.

It should be noted that the sum of squares of AC coefficients is closely related to the residual variance. Thus, according to the techniques described herein, the sum of squares of AC coefficients may be useful in determining a level of quantization. The residual variance, the sum of squares of AC coefficients, the number of significant level values present in a block, and the sum of the magnitude of AC coefficients may be described as a measure of activity in a TB. Thus, according to the techniques described herein, level of quantization performed on a block of video data (e.g., a TB) may be based on a measure of activity of AC coefficients. That is, in some cases it may be useful to adjust the level of quantization indicated by a predictive QP value based on a measure of activity of AC coefficients. However, it should be noted, as illustrated in FIG. 4B, a video decoder extracts coefficient level values from a bitstream and AC coefficients (and a resulting residual) are dependent on a dequantization process. Thus, a video decoder cannot directly determine a level of quantization based on a measure of activity determined from dequantized values.

According to the techniques described herein, coefficient quantization unit 206 may be configured to select the level of quantization, which includes a level of dequantization to be performed by an inverse quantization process based on one or more video coding properties according to the techniques described herein. In one example, coefficient quantization unit 206 may be configured to use a measure of activity of AC coefficients to modulate a level of quantization. In one example, coefficient quantization unit 206 may be configured such that a set of test candidates (e.g., {a₁, …, a_N}) are mapped to multiplicative adjustments (or offset adjustment), which may be used to adjust the level of quantization. For example, for a current block of video data, if a predictive QP corresponds to a scaling factor of 5, test candidates {a₁, a₂, a₃} may be mapped to the multipliers {1, 2, 3,}, which may result in respective resulting scaling factors of 5, 10, and 15.

In one example, coefficient quantization unit 206 may be configured to perform quantization on transform coefficients according to a set of test candidates, e.g., {a₁, …, a_N}. For example, referring to FIG. 4A and FIG. 7, in FIG. 7, quantization is performed on the group of transform coefficients using resulting scaling factors corresponding to a₁ and a₂. In this example, a QP value may correspond to the scaling factors illustrated in FIG. 4A and test candidate a₁ may map to scaling factors equal to the scaling factors illustrated in FIG. 4A and test candidate a₂ may map to scaling factors illustrated in FIG. 4A multiplied by two. Referring again to FIG. 7, each of test candidates a₁ and a₂ result in respective candidate coefficient level values l₁ and l₂. It should be noted that l₂ includes fewer significant level values than l₁ and as such, may require fewer bits to signal in a bitstream. It should be noted that in other examples, as described above, performing quantization on transform coefficients according to a set of test candidates may be implemented by scaling transform coefficients prior to performing quantization. FIG. 8 illustrates an example where transform coefficients are scaled prior to quantization. That is in the example illustrated in FIG. 8, a set of scaled transform coefficients are generated by multiplying the transform coefficients by 2.

Referring again to FIG. 6, quantized transform coefficients are output to inverse quantization/transform processing unit 208. Inverse quantization/transform processing unit 208 may be configured to apply an inverse quantization and an inverse transformation to generate reconstructed residual data. As further illustrated in FIG. 6, at summer 210, reconstructed residual data may be added to a predictive video block. In this manner, an encoded video block may be reconstructed and the resulting reconstructed video block may be used to evaluate the encoding quality for a given prediction, transformation, and/or quantization. Video encoder 200 may be configured to perform multiple coding passes (e.g., perform encoding while varying one or more of a prediction, transformation parameters, and quantization parameters). The rate-distortion of a bitstream or other system parameters may be optimized based on the evaluation of reconstructed video blocks. Further, reconstructed video blocks may be stored and used as reference for predicting subsequent blocks.

In a similar manner, coefficient quantization unit 206 may be configured to select a resulting level of quantization resulting from one of test candidates in a set of test candidates that provides a desired level of quantization. For example, for a current block of video data, if a predictive QP corresponds to a scaling factor of 5 and test candidates {a₁, a₂, a₃} are mapped to the multipliers {1, 2, 3,}, test candidate a₂ may be selected if a resulting scaling factor of 10 (i.e., 5*2) provides a desired level of quantization. In this manner, coefficient quantization unit 206 may evaluate respective resulting reconstructed video blocks for each test candidate in a set of test candidates and select a test candidate based on a desired coding result. That is, video encoder 200 may be configured to evaluate respective reconstructed blocks using reference video blocks and/or one or more other video coding properties in order to determine which set of coefficient level values is to be included in a bitstream, e.g., which set of coefficient level values achieves a desired bit-rate.

Referring to FIG. 9, the reconstructed block b₁ resulting from test candidate a₁ and level values l₁ and the reconstructed block b₂ resulting from test candidate a₂ and resulting l₂ in the example illustrated in FIG. 7 are illustrated. Referring to FIG. 10, the reconstructed block b₁ resulting from level values l₁ and the reconstructed block b₂ resulting from value values l₂ in the example illustrated in FIG. 8 are illustrated. It should be noted that in FIG. 9 and FIG. 10, for the sake of brevity, the intermediate operations for generating reconstructed blocks including inverse transformation and addition of a prediction and the residual are not illustrated. In each of the examples illustrated in FIG. 9 and FIG. 10, video encoder 200 may evaluate b₁ and b₂ to determine which set of coefficient level values is to be included in a bitstream.

As described above, a video decoder extracts coefficient level values from a bitstream and cannot directly determine a level of quantization based on a measure of activity determined from dequantized values and as such, a video encoder would typically send a delta QP value in order for a video decoder to adjust a level of quantization. According to the techniques described herein, video encoder 200 may be configured to select a test candidate from a set of test candidates that provides a desired level of quantization and further based on a video decoder being able to determine the selected test candidate based on properties of video data. That is, video encoder 200 may be configured to determine whether a video decoder can determine a selected test candidate, based on a known set of test candidates corresponding to respective adjustments to a level of quantization, coefficient level values included in a bitstream, and a recovery algorithm based on available properties of video data. That is, a video encoder and video decoder may be configured to derive a set of test candidates (e.g., test candidates may be included in a look-up table) and perform a recovery algorithm.

FIG. 12 illustrates an example where test candidate a₂ described with respect to the example illustrated in FIG. 7 has been selected. FIG. 13 illustrates an example where transform coefficients are scaled by 2 prior to quantization as provided in the example illustrated in FIG. 8. For each of the examples illustrated in FIG. 12 and FIG. 13, a recovery process includes receiving coefficient level values l₂. In the example illustrated in FIG. 12 for each of test candidate a₁and a₂ respective reconstructed blocks b₁ and b₂ are determined. Likewise in the example illustrated in FIG. 13 respective reconstructed blocks b₁ and b₂ are determined. A recovery algorithm may be performed for each of reconstructed blocks b₁ and b₂, in order to determine which of reconstructed blocks b₁ or b₂ corresponds to a current coded video block. That is, which of reconstructed block b₁ or b₂ will be output during a video decoding process. It should be noted that an ideal recovery algorithm would correctly select the reconstructed block at a video decoder in all cases (e.g., for all possible test candidates for all values of video data). However, a non-ideal recovery algorithm may, in some cases, provide undesirable results. For example, referring to the example illustrated in FIG. 12, a non-ideal recovery algorithm may result in a video decoder selecting a₁ and outputting b₁ instead of selecting a₂ and outputting b₂. It should be noted, however, that a video encoder performing the recovery algorithm may determine such cases and accommodate for such cases. For example, a video encoder may determine that the non-ideal result is acceptable (e.g., determine it is acceptable for a video decoder to output b₁ instead of b₂)) or determine that another test candidate should be selected.

In one example, a recovery algorithm may include a best match algorithm. In one example, video encoder 200 and a corresponding video decoder may be configured to compare the edges of respective reconstructed blocks (i.e., the reconstructed blocks resulting from the level values corresponding to the selected test candidate and respective test candidates included in a set of test candidates) with edges of neighboring previously reconstructed blocks and recover the selected test candidate based on which reconstructed block provides the best match with the neighboring edge values. In one example, video encoder 200 and a corresponding video decoder may determine which reconstructed block provides the best match according to the following equations:
-RL[X][y] for y = 0 to Y represents the right-most column of reconstructed luma (or chroma) samples for the left CU neighbor.

-RT[x][Y] for x = 0 to X represents the bottom-most row of reconstructed luma (or chroma) samples for the top CU neighbor.

-R_i[x][y] represents a reconstructed block corresponding to one of i ={a₁, …, a_N}, a set of test candidate scaling factors.

E[i] = sum( (RL[X][y] - R_i[0][y])^2 ) + sum( (RT[x][Y] - R_i[x][0])^2 ) over y = 0 to Y and respectively x = 0 to X for each i.

Where sum(x[i]) is a summation function.

Further, it should be noted that in one example, if either of RL[X][y] or RT[x][Y] are not available, the corresponding summation term may be disregarded (e.g., set to zero). In one example, a recovery algorithm may determine which test candidate was selected based on which reconstructed block provides the minimum value for E[i].

In the example above, E[i] is a sum of squared differences. In one example, E[i] may be a sum of absolute differences and may be based on the following equation:
E[i] = sum( abs(RL[X][y] - R_i[0][y]) ) + sum( abs(RT[x][Y] - R_i[x][0]) ) over y = 0 to Y and respectively x = 0 to X for each i.

Where sum(x[i]) is a summation function and abs(x) returns the absolute value of x.

It should be noted that in some cases, using a sum of absolute differences may improve the accuracy of a best match determination compared to using a sum of squared differences.

In one example, E[i] may be computed without including outlier difference values. For example, in each of the summations in the E[i] calculations above, the largest N (e.g., N = 2) difference values may be excluded from the summation. For example, if abs(RL[X][2] - R_i[0][2]) provides the largest value over y = 0 to Y, it may be excluded from the sum( abs(RL[X][y] - R_i[0][y]) ) calculation in the case where N = 1.

It should be noted that in the equations above, R_i[x][y] = r_i[x][y]+p[x][y], where r_i[x][y] is the residual corresponding to one of i ={a₁, …, a_N} and p[x][y] is the set of prediction values associated with the current block. Further, referring to the example illustrated in FIG. 13, transform coefficients T₁, may be considered transform coefficients that result from a video decoder performing a standard inverse quantization. That is, a video decoder generates transform coefficients T₁ without performing respective inverse scaling based on each of the test candidates. In this manner, the resulting residual from transform coefficients T₁ may be referred to as r₁[x][y]. In one example, a matching algorithm may be based on the following equation, R’_i[x][y] = r₁[x][y]/s[i] + p[x][y], where s[i] is a factor corresponding to one of i ={a₁, …, a_N}. For example, R_i[x][y] in the equations above may be substituted with R’_i[x][y] and a recovery algorithm may determine which test candidate was selected based on which test candidate provides the minimum value for E[i]. It should be noted that in this example, for the selected test candidate, a corresponding inverse scaling operation would be performed on the received coefficient level values in order to generate transform coefficients T_iand corresponding r_i[x][y] used for reconstruction. Further, it should be noted that in some cases, the corresponding r_i[x][y] used for reconstruction may be equal to r₁[x][y]. Using R’_i[x][y] for a recovery algorithm may be particularly useful when there is a relatively large number of test candidates. That is, a respective inverse transform operation is required to generate each r_i[x][y] for i ={a₁, …, a_N}. To generate each R’_i[x][y] for i ={a₁, …, a_N}, a single inverse transform operation is required.

In one example, a recovery algorithm may be based on the average of sample values of a reconstructed block corresponding to respective test candidates {a₁, …, a_N}. In one example, video encoder 200 and a corresponding video decoder may be configured to compare respective reconstructed DC coefficients plus the average of sample values of a prediction block to the average of sample values of neighboring blocks. In one example, video encoder 200 and a corresponding video decoder may determine which test candidate was selected by the encoder based on which average of sample values most closely matches its neighbors. In one example, a matching equation may be based on the following equations:
-DC_L represents the average of sample values for the left CU neighbor.

-DC_T represents the average of sample values for the top CU neighbor.

-DC_i represents a reconstructed DC coefficient corresponding to one of i ={a₁, …, a_N} plus the average of sample values of a prediction block.

F[i] = (DC_L - DC_i)^2 + (DC_T - DC_i)^2
In one example, a recovery algorithm may determine which test candidate was selected based on which reconstructed block provides the minimum value for F[i].

In this manner, video encoder 200 represents an example of a device configured to receive an array of transform coefficient values, for each test candidate in a set of test candidates, generate a reconstructed block of video data corresponding to the array of transform coefficients, select one of the test candidates based a respective reconstructed block of video data and a property of video data, and output level values corresponding to the selected test candidate.

As described above, a recovery algorithm may include a best match algorithm based on reconstructed sample values included in the right-most column of the left CU neighbor and reconstructed sample values included in the bottom-most row of the top CU neighbor. In some cases, it may be useful to perform a best match algorithm using a subset of samples in the right-most column of the left CU neighbor and/or a subset of samples in the bottom-most row of the top CU neighbor. For example, in the equations for E[i] above, x may be over 0 to X for i = {0, 2, 4, …, X} and/or y may be over 0 to Y for i = {0, 2, 4, …, Y}. That is, a difference value may be determined for every other sample value.

In one example, a difference value may be determined over (X+1)/2 and/or (Y+1)/2. Each of (X+1)/2 and (Y+1)/2 may be referred to as number of edge samples divided by two, i.e., numEdgeSamples/2. In one example, a difference value may be determined for contiguous sets of numEdgeSamples/N samples, where N is an integer (e.g., 2). The contiguous sets may include samples in the right-most column of the left CU neighbor and/or in the bottom-most row of the top CU neighbor, where the first sample in each contiguous set is defined by a y value equal to {0…Y} for contiguous sets in the right-most column of the left CU neighbor and by a x value equal to {0…X} for contiguous sets for the bottom-most row of the top CU neighbor. That is, an offset value may specify a contiguous set of samples having a defined length. In one example, using contiguous sets may be described conceptually as determining a difference metric for each position of a sliding window.

In one example, a contiguous set of samples used for a best match algorithm may be determined based on an indication of prediction quality. For example, a prediction block (e.g., a block generated using an inter prediction technique), a reconstructed top CU neighbor, and a reconstructed left CU neighbor may be used to determine a contiguous set of samples used for a best match algorithm. For example, the sample values in the top row of the prediction block may be compared to sample values in the bottom-most row of the reconstructed above CU neighbor and/or sample values in the left column of the prediction block may be compared to sample values in the right-most column of the reconstructed left CU neighbor. For example, a sliding window may be used to generate difference values for sample values in the prediction block and the neighboring CUs. In one example, a difference value providing the greatest value may be referred to as loc_worst. In one example, an algorithm may determine a loc_worst value (e.g., top row loc_worst or a left column loc_worst value). The offsets corresponding to the loc_worst value (e.g., x = 5, y = 4) may be used in a recovery algorithm for each test candidate scaling factor. For example, in the calculations of E[i] provided above, x and y may be over numEdgeSamples/N starting at the offsets corresponding to the loc_worst value.

In one example, loc_worst may be determined for the top edge and the left edge of a current reconstructed block. Table 1 includes an example of pseudocode that may be used to determine a loc_worst for the left edge of a current reconstructed block.

In Table 1, prediction represents a prediction associated with the current block and recLeftBlk_RightEdge(i) provides a sample value in the right-most column of the left CU neighbor.

In one example, a smoothing filter may be applied to reconstructed blocks corresponding to test candidate scaling factors and neighboring blocks prior to performing a recovery algorithm (e.g., prior to calculating E[i]). In some cases, applying a smoothing filter prior to performing a recovery algorithm may improve the accuracy of the recovery algorithm. For example, in one example, a 5-tap finite impulse response (FIR) filter, (e.g., [.1 .175 .45 .175 .1]), may be applied to samples included in the top row of the current block and samples included in the bottom-most row of the neighboring above block. Similarly, a 5-tap FIR filter may be applied to samples included in the left column of the current block and samples included in the right-most column of the neighboring left block.

As described above, a video block may be coded using an intra prediction. Intra prediction processing unit 212 may be configured to select an intra prediction mode for a video block to be coded. Intra prediction processing unit 212 may be configured to evaluate a frame and/or an area thereof and determine an intra prediction mode to use to encode a current block. As illustrated in FIG. 6, intra prediction processing unit 212 outputs intra prediction data (e.g., syntax elements) to entropy encoding unit 218 and transform coefficient generator 204. As described above, a transform performed on residual data may be mode dependent. As described above, possible intra prediction modes may include planar prediction modes, DC prediction modes, and angular prediction modes. Further, in some examples, a prediction for a chroma component may be inferred from an intra prediction for a luma prediction mode.

Inter prediction processing unit 214 may be configured to perform inter prediction coding for a current video block. Inter prediction processing unit 214 may be configured to receive source video blocks and calculate a motion vector for PUs of a video block. A motion vector may indicate the displacement of a PU (or similar coding structure) of a video block within a current video frame relative to a predictive block within a reference frame. Inter prediction coding may use one or more reference pictures. Further, motion prediction may be uni-predictive (use one motion vector) or bi-predictive (use two motion vectors). Inter prediction processing unit 214 may be configured to select a predictive block by calculating a pixel difference determined by, for example, sum of absolute difference (SAD), sum of square difference (SSD), or other difference metrics. As described above, a motion vector may be determined and specified according to motion vector prediction. Inter prediction processing unit 214 may be configured to perform motion vector prediction, as described above. Inter prediction processing unit 214 may be configured to generate a predictive block using the motion prediction data. For example, inter prediction processing unit 214 may locate a predictive video block within a frame buffer (not shown in FIG. 6). It should be noted that inter prediction processing unit 214 may further be configured to apply one or more interpolation filters to a reconstructed residual block to calculate sub-integer pixel values for use in motion estimation. Inter prediction processing unit 214 may output motion prediction data for a calculated motion vector to entropy encoding unit 218. As illustrated in FIG. 6, inter prediction processing unit 214 may receive reconstructed video block via post filter unit 216. Post filter unit 216 may be configured to perform deblocking and/or Sample Adaptive Offset (SAO) filtering. Deblocking refers to the process of smoothing the boundaries of reconstructed video blocks (e.g., make boundaries less perceptible to a viewer). SAO filtering is a non-linear amplitude mapping that may be used to improve reconstruction by adding an offset to reconstructed video data.

Referring again to FIG. 6, entropy encoding unit 218 receives quantized transform coefficients and predictive syntax data (i.e., intra prediction data, motion prediction data, QP data, etc.). It should be noted that in some examples, coefficient quantization unit 206 may perform a scan of a matrix including quantized transform coefficients before the coefficients are output to entropy encoding unit 218. In other examples, entropy encoding unit 218 may perform a scan. Entropy encoding unit 218 may be configured to perform entropy encoding according to one or more of the techniques described herein. Entropy encoding unit 218 may be configured to output a compliant bitstream, i.e., a bitstream that a video decoder can receive and reproduce video data therefrom.

FIG. 11 is a block diagram illustrating an example of a video decoder that may be configured to decode video data according to one or more techniques of this disclosure. In one example, video decoder 300 may be configured to reconstruct video data based on one or more of the techniques described above. That is, video decoder 300 may operate in a reciprocal manner to video encoder 200 described above. Video decoder 300 may be configured to perform intra prediction decoding and inter prediction decoding and, as such, may be referred to as a hybrid decoder. In the example illustrated in FIG. 11 video decoder 300 includes an entropy decoding unit 302, inverse quantization unit 304, inverse transformation processing unit 306, intra prediction processing unit 308, inter prediction processing unit 310, summer 312, post filter unit 314, and reference buffer 316. Video decoder 300 may be configured to decode video data in a manner consistent with a video encoding system, which may implement one or more aspects of a video coding standard. It should be noted that although example video decoder 300 is illustrated as having distinct functional blocks, such an illustration is for descriptive purposes and does not limit video decoder 300 and/or sub-components thereof to a particular hardware or software architecture. Functions of video decoder 300 may be realized using any combination of hardware, firmware, and/or software implementations.

As illustrated in FIG. 11, entropy decoding unit 302 receives an entropy encoded bitstream. Entropy decoding unit 302 may be configured to decode quantized syntax elements and quantized coefficients from the bitstream according to a process reciprocal to an entropy encoding process. Entropy decoding unit 302 may be configured to perform entropy decoding according any of the entropy coding techniques described above. Entropy decoding unit 302 may parse an encoded bitstream in a manner consistent with a video coding standard. Video decoder 300 may be configured to parse an encoded bitstream where the encoded bitstream is generated based on the techniques described above.

Referring again to FIG. 11, inverse quantization unit 304 receives quantized transform coefficients (i.e., level values) and quantization parameter data from entropy decoding unit 302. Quantization parameter data may include any and all combinations of delta QP values and/or quantization group size values and the like described above. Video decoder 300 and/or inverse quantization unit 304 may be configured to determine QP values used for inverse quantization based on values signaled by a video encoder and/or through video properties and/or coding parameters. That is, inverse quantization unit 304 may operate in a reciprocal manner to coefficient quantization unit 206 described above. Inverse quantization unit 304 may be configured to apply an inverse quantization. Inverse transform processing unit 306 may be configured to perform an inverse transformation to generate reconstructed residual data. The techniques respectively performed by inverse quantization unit 304 and inverse transform processing unit 306 may be similar to techniques performed by inverse quantization/transform processing unit 208 described above. Inverse transform processing unit 306 may be configured to apply an inverse DCT, an inverse DST, an inverse integer transform, Non-Separable Secondary Transform (NSST), or a conceptually similar inverse transform processes to the transform coefficients in order to produce residual blocks in the pixel domain. Further, as described above, whether a particular transform (or type of particular transform) is performed may be dependent on an intra prediction mode. As illustrated in FIG. 11, reconstructed residual data may be provided to summer 312. Summer 312 may add reconstructed residual data to a predictive video block and generate reconstructed video data. A predictive video block may be determined according to a predictive video technique (i.e., intra prediction and inter frame prediction).

As described above, a video encoder may be configured to select a test candidate from a set of test candidates based on the evaluation of respective resulting reconstructed video blocks. Video decoder 300 may be configured to receive a set of coefficient level values and determine which test candidate was selected and should be used to reconstruct video data. In one example, video decoder 300 may be configured to receive a set of coefficient level values and generate a reconstructed video block for each test candidate factor. As described above, FIG. 12 corresponds to an example where a video decoder receives coefficient level values l₂ illustrated in the example of FIG. 7 above. FIG. 13 illustrates an example where a video decoder receives coefficient level values l₂ illustrated in the example of FIG. 8 above. Referring to the examples illustrated in FIG. 12 and FIG. 13, for the received coefficient level values, video decoder 300 may generate reconstructed blocks corresponding to the test candidates. Video decoder 300 may evaluate each of reconstructed blocks in order to determine which reconstructed block to output. Further, as described above, in some examples, video decoder 300 may evaluate a residual that is respectively scaled corresponding to each test candidate. In one example, video decoder 300 may perform a matching algorithm as described above. For example, video decoder 300 may select the reconstructed block based on which reconstructed block minimizes the value of E[i] or F[i].

In this manner, video decoder 300 represents an example of a device configured to receive an array of level values, for each test candidate in a set of test candidates, generate a respective block of video data, select a test candidate based on a respective block of video data and a property of video data, and output a reconstructed block of video data corresponding to the selected test candidate.

Intra prediction processing unit 308 may be configured to receive intra prediction syntax elements and retrieve a predictive video block from reference buffer 316. Reference buffer 316 may include a memory device configured to store one or more frames of video data. Intra prediction syntax elements may identify an intra prediction mode, such as the intra prediction modes described above. In one example, intra prediction processing unit 308 may reconstruct a video block using according to one or more of the intra prediction coding techniques described herein. Inter prediction processing unit 310 may receive inter prediction syntax elements and generate motion vectors to identify a prediction block in one or more reference frames stored in reference buffer 316. Inter prediction processing unit 310 may produce motion compensated blocks, possibly performing interpolation based on interpolation filters. Identifiers for interpolation filters to be used for motion estimation with sub-pixel precision may be included in the syntax elements. Inter prediction processing unit 310 may use interpolation filters to calculate interpolated values for sub-integer pixels of a reference block. Post filter unit 314 may be configured to perform filtering on reconstructed video data. For example, post filter unit 314 may be configured to perform deblocking and/or SAO filtering, as described above with respect to post filter unit 216. Further, it should be noted that in some examples, post filter unit 314 may be configured to perform proprietary discretionary filter (e.g., visual enhancements). As illustrated in FIG. 11, a reconstructed video block may be output by video decoder 300. In this manner, video decoder 300 may be configured to generate reconstructed video data according to one or more of the techniques described herein.

In one or more examples, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium and executed by a hardware-based processing unit. Computer-readable media may include computer-readable storage media, which corresponds to a tangible medium such as data storage media, or communication media including any medium that facilitates transfer of a computer program from one place to another, e.g., according to a communication protocol. In this manner, computer-readable media generally may correspond to (1) tangible computer-readable storage media which is non-transitory or (2) a communication medium such as a signal or carrier wave. Data storage media may be any available media that can be accessed by one or more computers or one or more processors to retrieve instructions, code and/or data structures for implementation of the techniques described in this disclosure. A computer program product may include a computer-readable medium.

By way of example, and not limitation, such computer-readable storage media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage, or other magnetic storage devices, flash memory, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer. Also, any connection is properly termed a computer-readable medium. For example, if instructions are transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. It should be understood, however, that computer-readable storage media and data storage media do not include connections, carrier waves, signals, or other transitory media, but are instead directed to non-transitory, tangible storage media. Disk and disc, as used herein, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

Instructions may be executed by one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors, application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Accordingly, the term “processor,” as used herein may refer to any of the foregoing structure or any other structure suitable for implementation of the techniques described herein. In addition, in some aspects, the functionality described herein may be provided within dedicated hardware and/or software modules configured for encoding and decoding, or incorporated in a combined codec. Also, the techniques could be fully implemented in one or more circuits or logic elements.

The techniques of this disclosure may be implemented in a wide variety of devices or apparatuses, including a wireless handset, an integrated circuit (IC) or a set of ICs (e.g., a chip set). Various components, modules, or units are described in this disclosure to emphasize functional aspects of devices configured to perform the disclosed techniques, but do not necessarily require realization by different hardware units. Rather, as described above, various units may be combined in a codec hardware unit or provided by a collection of interoperative hardware units, including one or more processors as described above, in conjunction with suitable software and/or firmware.

Moreover, each functional block or various features of the base station device and the terminal device used in each of the aforementioned embodiments may be implemented or executed by a circuitry, which is typically an integrated circuit or a plurality of integrated circuits. The circuitry designed to execute the functions described in the present specification may comprise a general-purpose processor, a digital signal processor (DSP), an application specific or general application integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gates or transistor logic, or a discrete hardware component, or a combination thereof. The general-purpose processor may be a microprocessor, or alternatively, the processor may be a conventional processor, a controller, a microcontroller or a state machine. The general-purpose processor or each circuit described above may be configured by a digital circuit or may be configured by an analogue circuit. Further, when a technology of making into an integrated circuit superseding integrated circuits at the present time appears due to advancement of a semiconductor technology, the integrated circuit by this technology is also able to be used.

Various examples have been described. These and other examples are within the scope of the following claims.

<overview>
In one example, a method of coding of video data comprises receiving an array of transform coefficient values, for each test candidate in a set of test candidates, generating a reconstructed block of video data corresponding to the array of transform coefficients, selecting one of the test candidates based a respective reconstructed block of video data and a property of video data, and outputting level values corresponding to the selected test candidate.

In one example, a device for coding video data comprises one or more processors configured to receive an array of transform coefficient values, for each test candidate in a set of test candidates, generate a reconstructed block of video data corresponding to the array of transform coefficients, select one of the test candidates based a respective reconstructed block of video data and a property of video data, and output level values corresponding to the selected test candidate.

In one example, a non-transitory computer-readable storage medium comprises instructions stored thereon that, when executed, cause one or more processors of a device to receive an array of transform coefficient values, for each test candidate in a set of test candidates, generate a reconstructed block of video data corresponding to the array of transform coefficients, select one of the test candidates based a respective reconstructed block of video data and a property of video data, and output level values corresponding to the selected test candidate.

In one example, an apparatus comprises means for receiving an array of transform coefficient values, means for generating a reconstructed block of video data corresponding to the array of transform coefficients for each test candidate in a set of test candidates, means for selecting one of the test candidates based a respective reconstructed block of video data and a property of video data, and means for outputting level values corresponding to the selected test candidate.

In one example, a method of coding of video data comprises receiving an array of level values, for each test candidate in a set of test candidates, generating a respective block of video data, selecting a test candidate based on a respective block of video data and a property of video data, and outputting a reconstructed block of video data corresponding to the selected test candidate.

In one example, a device for coding video data comprises one or more processors configured to receive an array of level values, for each test candidate in a set of test candidates, generate a respective block of video data, select a test candidate based on a respective block of video data and a property of video data, and output a reconstructed block of video data corresponding to the selected test candidate.

In one example, a non-transitory computer-readable storage medium comprises instructions stored thereon that, when executed, cause one or more processors of a device to receive an array of level values, for each test candidate in a set of test candidates, generate a respective block of video data, select a test candidate based on a respective block of video data and a property of video data, and output a reconstructed block of video data corresponding to the selected test candidate.

In one example, an apparatus comprises means for receiving an array of level values, means for generating a respective block of video data for each test candidate in a set of test candidates, means for selecting a test candidate based on a respective block of video data and a property of video data, and means for outputting a reconstructed block of video data corresponding to the selected test candidate.

<Cross Reference>
This Nonprovisional application claims priority under 35 U.S.C. § 119 on provisional Application No. 62/477,861 on March 28, 2017 and provisional Application No. 62/513,406 on May 31, 2017, the entire contents of which are hereby incorporated by reference.

Claims

A method of coding of video data, the method comprising:
receiving an array of transform coefficient values;
for each test candidate in a set of candidates, generating a reconstructed block of video data corresponding to the array of transform coefficients;
selecting one of the test candidates based on a respective reconstructed block of video data and a property of video data; and
outputting level values corresponding to the selected test candidate.
The method of claim 1, wherein selecting one of the test candidates based on a respective reconstructed block of video data and a property of video data includes selecting a test candidate based on a recovery algorithm.
The method claim 2, wherein a recovery algorithm includes a best match recovery algorithm.
A method of coding of video data, the method comprising:
receiving an array of level values;
for each test candidate in a set of test candidates, generating a respective block of video data;
selecting a test candidate based on a respective block of video data and a property of video data; and
outputting a reconstructed block of video data corresponding to the selected test candidate.
The method of claim 4, wherein selecting a test candidate based on a respective block of video data and a property of video data includes selecting a test candidate based on a reconstructed block of video data providing a best match with neighboring video blocks.
The method claim 5, wherein providing a best match with neighboring video blocks includes having a minimum difference compared the edges of a neighboring top block and a neighboring left block.
A device for coding video data, the device comprising one or more processors configured to perform any and all combinations of the steps of claims 1-6.
The device of claim 7, wherein the device includes a video encoder.
The device of claim 7, wherein the device includes a video decoder.
A system comprising:
the device of claim 8; and
the device of claim 9.
An apparatus for coding video data, the apparatus comprising means for performing any and all combinations of the steps of claims 1-6.
A non-transitory computer-readable storage medium comprising instructions stored thereon that, when executed, cause one or more processors of a device for coding video data to perform any and all combinations of the steps of claims 1-6.