WO2016090568A1 - Binary tree block partitioning structure - Google Patents

Binary tree block partitioning structure Download PDF

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Publication number
WO2016090568A1
WO2016090568A1 PCT/CN2014/093445 CN2014093445W WO2016090568A1 WO 2016090568 A1 WO2016090568 A1 WO 2016090568A1 CN 2014093445 W CN2014093445 W CN 2014093445W WO 2016090568 A1 WO2016090568 A1 WO 2016090568A1
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Prior art keywords
binary tree
splitting
partitioning
block
size
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PCT/CN2014/093445
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French (fr)
Inventor
Jicheng An
Kai Zhang
Original Assignee
Mediatek Singapore Pte. Ltd.
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Priority to PCT/CN2014/093445 priority Critical patent/WO2016090568A1/en
Priority to MX2017007235A priority patent/MX367953B/en
Priority to CN202010118749.1A priority patent/CN111314695B/en
Priority to CN201580067076.9A priority patent/CN107005718B/en
Priority to EP15868304.5A priority patent/EP3213514A4/en
Priority to CA2966522A priority patent/CA2966522C/en
Priority to BR112017011889A priority patent/BR112017011889A8/en
Priority to KR1020177014473A priority patent/KR102014618B1/en
Priority to PCT/CN2015/096761 priority patent/WO2016091161A1/en
Priority to RU2017116191A priority patent/RU2665311C1/en
Priority to SG10201805297RA priority patent/SG10201805297RA/en
Priority to EP22186408.5A priority patent/EP4096220A1/en
Priority to US15/532,166 priority patent/US9843804B2/en
Priority to SG11201703552WA priority patent/SG11201703552WA/en
Publication of WO2016090568A1 publication Critical patent/WO2016090568A1/en
Priority to MX2019010795A priority patent/MX2019010795A/en
Priority to US15/801,457 priority patent/US10375393B2/en
Priority to US15/830,392 priority patent/US10382795B2/en
Priority to US16/451,300 priority patent/US10506231B2/en

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/119—Adaptive subdivision aspects, e.g. subdivision of a picture into rectangular or non-rectangular coding blocks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/146—Data rate or code amount at the encoder output
    • H04N19/147—Data rate or code amount at the encoder output according to rate distortion criteria
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H04N19/174—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a slice, e.g. a line of blocks or a group of blocks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H04N19/176—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a block, e.g. a macroblock
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/90—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using coding techniques not provided for in groups H04N19/10-H04N19/85, e.g. fractals
    • H04N19/96—Tree coding, e.g. quad-tree coding
    • G—PHYSICS
    • G02—OPTICS
    • G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
    • G02B27/00—Optical systems or apparatus not provided for by any of the groups G02B1/00 - G02B26/00, G02B30/00
    • G02B27/10—Beam splitting or combining systems
    • G02B27/14—Beam splitting or combining systems operating by reflection only
    • G02B27/145—Beam splitting or combining systems operating by reflection only having sequential partially reflecting surfaces
    • G02B27/146—Beam splitting or combining systems operating by reflection only having sequential partially reflecting surfaces with a tree or branched structure
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T9/00—Image coding
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T9/00—Image coding
    • G06T9/005—Statistical coding, e.g. Huffman, run length coding
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T9/00—Image coding
    • G06T9/20—Contour coding, e.g. using detection of edges
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N13/00—Stereoscopic video systems; Multi-view video systems; Details thereof
    • H04N13/10—Processing, recording or transmission of stereoscopic or multi-view image signals
    • H04N13/189—Recording image signals; Reproducing recorded image signals

Definitions

  • the invention relates generally to video processing.
  • the present invention relates to methods and apparatuses for block partitioning structure in video and image coding.
  • the High Efficiency Video Coding (HEVC) standard is the most recent joint video project of the ITU-T Video Coding Experts Group (VCEG) and the ISO/IEC Moving Picture Experts Group (MPEG) standardization organizations, working together in a partnership known as the Joint Collaborative Team on Video Coding (JCT-VC) .
  • VCEG Video Coding Experts Group
  • MPEG Moving Picture Experts Group
  • one slice is partitioned into multiple coding tree units (CTU) .
  • CTU coding tree units
  • SPS sequence parameter set
  • a raster scan method is used for processing the CTU.
  • the CTU is further partitioned into multiple coding units (CU) to adapt to various local characteristics.
  • a quadtree denoted as the coding tree is used to partition the CTU into multiple CUs.
  • CTU size be M ⁇ M where M is one of the values of 64, 32, or 16.
  • the CTU can be a single CU or can be split into four smaller units of equal sizes of M/2 ⁇ M/2, which are nodes of coding tree. If units are leaf nodes of coding tree, the units become CUs. Otherwise, the quadtree splitting process can be iterated until the size for a node reaches a minimum allowed CU size specified in the SPS. This representation results in a recursive structure specified by a coding tree as shown in Fig. 1.
  • the solid lines indicate CU boundaries.
  • the decision whether to code a picture area using interpicture (temporal) or intrapicture (spatial) prediction is made at the CU level. Since the minimum CU size can be 8 ⁇ 8, the minimum granularity for switching different basic prediction type is 8 ⁇ 8.
  • One or more prediction units are specified for each CU. Coupled with the CU, the PU works as a basic representative block for sharing the prediction information. Inside one PU, the same prediction process is applied and the relevant information is transmitted to the decoder on a PU basis.
  • a CU can be split into one, two, or four PUs according to the PU splitting type.
  • HEVC defines eight shapes for splitting a CU into PU as shown in Fig. 2. Unlike the CU, the PU may only be split once.
  • a CU After obtaining the residual block by prediction process based on PU splitting type, a CU can be partitioned into transform units (TU) according to another quadtree structure which is analogous to the coding tree for the CU as shown in Fig. 1.
  • the solid lines indicate CU boundaries and dotted lines indicate TU boundaries.
  • the TU is a basic representative block having residual or transform coefficients for applying the integer transform and quantization. For each TU, one integer transform having the same size to the TU is applied to obtain residual coefficients. These coefficients are transmitted to the decoder after quantization on a TU basis.
  • coding tree block CB
  • CB coding block
  • PB prediction block
  • TB transform block
  • the tree partitioning is generally applied simultaneously to both luma and chroma, although exceptions apply when certain minimum sizes are reached for chroma.
  • the coding efficiency is still not sufficient to cope with the ever increasing demands for storage and transmission of video content.
  • a binary tree structure is proposed for partitioning a unit into multiple smaller units such as partitioning a slice into CTUs, a CTU into CUs, a CU into PUs, or a CU into TUs, and so on.
  • the binary tree structure can be combined with quadtree structure, which is a quadtree plus binary tree (QTBT) structure.
  • QTBT binary tree
  • the root unit is firstly partitioned by a quadtree structure, then the leaf nodes of the quadtree is further partitioned by a binary tree structure.
  • Some parameters for restriction of the quadtree and binary tree can be defined in high level such as in SPS.
  • Fig. 1 illustrates the subdivision of a CTU into CUs and TUs (left) and its corresponding quadtree (right) in HEVC.
  • Fig. 2 illustrates the types for splitting a CU into PUs in HEVC.
  • Fig. 3 illustrates the possible splitting types in the proposed binary tree.
  • Fig. 4 illustrates an example of block partitioning (left) and its corresponding binary tree (right) .
  • Fig. 5 illustrates an example of block partitioning (left) and its corresponding quadtree plus binary tree (right) .
  • a binary tree block partitioning structure is proposed.
  • a block can be recursively split into two smaller blocks.
  • a flag signals whether it is split into two smaller blocks. If yes, another syntax element is signaled to indicate which splitting type is used. If the horizontal splitting is used then it is split into two blocks of size M ⁇ N/2, otherwise if the vertical splitting is used then it is split into two blocks of size M/2 ⁇ N.
  • the binary tree splitting process can be iterated until the size (width or height) for a splitting block reaches a minimum allowed block size (width or height) that can be defined in high level syntax such as SPS. Since the binary tree has two splitting types horizontal and vertical, so the minimum allowed block width and height should be both indicated. Not horizontal splitting is implicit when splitting would result in a block height smaller than the indicated minimum. Not vertical splitting is implicit when splitting would result in a block width smaller than the indicated minimum.
  • Fig. 4 illustrates an example of block partitioning (left) and its corresponding binary tree (right) . In each splitting (i.e., non-leaf) node of the binary tree, one flag indicates which splitting type (horizontal or vertical) is used, 0 indicates horizontal splitting and 1 indicates vertical splitting.
  • the proposed binary tree structure can be used for partitioning a block into multiple smaller blocks such as partitioning a slice into CTUs, a CTU into CUs, a CU into PUs, or a CU into TUs, and so on.
  • the binary tree for partitioning a CTU into CUs i.e., the root node of the binary tree is a CTU and the leaf node of the binary tree is CU, the leaf nodes are further processed by prediction and transform coding.
  • Quadtree plus binary tree (QTBT) structure In order to balance the complexity and coding efficiency, it is proposed to combine the quadtree and binary tree structure, which is called as quadtree plus binary tree (QTBT) structure.
  • QTBT binary tree plus binary tree
  • a block is firstly partitioned by a quadtree structure, the quadtree splitting can be iterated until the size for a splitting block reaches the minimum allowed quadtree leaf node size.
  • the leaf quadtree block is not larger than the maximum allowed binary tree root node size, it can be further partitioned by a binary tree structure, the binary tree splitting can be iterated until the size (width or height) for a splitting block reaches the minimum allowed binary tree leaf node size (width or height) or the binary tree depth reaches the maximum allowed binary tree depth.
  • the minimum allowed quadtree leaf node size, the maximum allowed binary tree root node size, the minimum allowed binary tree leaf node width and height, and the maximum allowed binary tree depth can be indicated in the high level syntax such as in SPS.
  • Fig. 5 illustrates an example of block partitioning (left) and its corresponding QTBT (right) .
  • the solid lines indicate quadtree splitting and dotted lines indicate binary tree splitting.
  • each splitting (i.e., non-leaf) node of the binary tree one flag indicates which splitting type (horizontal or vertical) is used, 0 indicates horizontal splitting and 1 indicates vertical splitting.
  • the proposed QTBT structure can be used for partitioning a block into multiple smaller blocks such as partitioning a slice into CTUs, a CTU into CUs, a CU into PUs, or a CU into TUs, and so on.
  • the QTBT for partitioning a CTU into CUs, i.e., the root node of the QTBT is a CTU which is partitioned into multiple CUs by a QTBT structure, and the CUs are further processed by prediction and transform coding.
  • the CTU is partitioned by a quadtree structure and the leaf quadtree unit may have size from 16 ⁇ 16 (minimum allowed quadtree leaf node size) to 128 ⁇ 128 (equal to CTU size, i.e., no split) , if the leaf quadtree unit is 128 ⁇ 128 it cannot be further split by binary tree since the size exceeds the maximum allowed binary tree root node size 64 ⁇ 64, otherwise the leaf quadtree unit can be further split by binary tree, the leaf quadtree unit which is also the root binary tree unit has binary tree depth as 0.
  • the leaf nodes of the QTBT are further processed by prediction (intrapicture or interpicture) and transform coding.
  • the proposed tree structure is applied separately to luma and chroma for I slice, and applied simultaneously to both luma and chroma (except when certain minimum sizes are reached for chroma) for P and B slice. That is to say that, in I slice, the luma CTB has its QTBT-structured block partitioning, and the two chroma CTBs has another QTBT-structured block partitioning, wherein as another embodiment, the two chroma CTBs can also have their own QTBT-structured block partitionings.
  • an embodiment of the present invention can be a circuit integrated into a video compression chip or program codes integrated into video compression software to perform the processing described herein.
  • An embodiment of the present invention may also be program codes to be executed on a Digital Signal Processor (DSP) to perform the processing described herein.
  • DSP Digital Signal Processor
  • the invention may also involve a number of functions to be performed by a computer processor, a digital signal processor, a microprocessor, or field programmable gate array (FPGA) .
  • processors can be configured to perform particular tasks according to the invention, by executing machine-readable software code or firmware code that defines the particular methods embodied by the invention.
  • the software code or firmware codes may be developed in different programming languages and different format or style.
  • the software code may also be compiled for different target platform.
  • different code formats, styles and languages of software codes and other means of configuring code to perform the tasks in accordance with the invention will not depart from the spirit and scope of the invention.

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Abstract

A binary tree block partitioning structure is proposed. The proposed flexible block partitioning structure plays an important role in the substantial performance gains relative the HEVC.

Description

BINARY TREE BLOCK PARTITIONING STRUCTURE TECHNICAL FIELD
The invention relates generally to video processing. In particular, the present invention relates to methods and apparatuses for block partitioning structure in video and image coding.
BACKGROUND
The High Efficiency Video Coding (HEVC) standard is the most recent joint video project of the ITU-T Video Coding Experts Group (VCEG) and the ISO/IEC Moving Picture Experts Group (MPEG) standardization organizations, working together in a partnership known as the Joint Collaborative Team on Video Coding (JCT-VC) .
In HEVC, one slice is partitioned into multiple coding tree units (CTU) . In main profile, the minimum and the maximum sizes of CTU are specified by the syntax elements in the sequence parameter set (SPS) among the sizes of 8x8, 16x16, 32×32, and 64×64. Inside a slice, a raster scan method is used for processing the CTU.
The CTU is further partitioned into multiple coding units (CU) to adapt to various local characteristics. A quadtree denoted as the coding tree is used to partition the CTU into multiple CUs. Let CTU size be M×M where M is one of the values of 64, 32, or 16. The CTU can be a single CU or can be split into four smaller units of equal sizes of M/2×M/2, which are nodes of coding tree. If units are leaf nodes of coding tree, the units become CUs. Otherwise, the quadtree splitting process can be iterated until the size for a node reaches a minimum allowed CU size specified in the SPS. This representation results in a recursive structure specified by a coding tree as shown in Fig. 1. The solid lines indicate CU boundaries. The decision whether to code a picture area using interpicture (temporal) or intrapicture (spatial) prediction is made at the CU level. Since the minimum CU size can be 8×8, the minimum granularity for switching different basic prediction type is 8×8.
One or more prediction units (PU) are specified for each CU. Coupled with the CU, the PU works as a basic representative block for sharing the prediction information. Inside one PU, the same prediction process is applied and the relevant information is transmitted to the decoder on a PU basis. A CU can be split into one, two, or four PUs according to the PU splitting type. HEVC defines eight shapes for splitting a CU into PU as shown in Fig. 2. Unlike the CU, the PU may only be split once.
After obtaining the residual block by prediction process based on PU splitting type, a CU can be partitioned into transform units (TU) according to another quadtree structure which is analogous to the coding tree for the CU as shown in Fig. 1. The solid lines indicate CU boundaries and dotted lines indicate TU boundaries. The TU is a basic representative block having residual or transform coefficients for applying the integer transform and quantization. For each TU, one integer transform having the same size to the TU is applied to obtain residual coefficients. These coefficients are transmitted to the decoder after quantization on a TU basis.
The terms coding tree block (CTB) , coding block (CB) , prediction block (PB) , and transform block (TB) are defined to specify the 2-D sample array of one color component associated with CTU, CU, PU, and TU, respectively. Thus, a CTU consists of one luma CTB, two chroma CTBs, and associated syntax elements. A similar relationship is valide for CU, PU, and TU.
The tree partitioning is generally applied simultaneously to both luma and chroma, although exceptions apply when certain minimum sizes are reached for chroma.
However, due to some restrictions in the current HEVC block partitioning structure, e. g. , the quadtree based partitioning from CTU to CU and from CU to TU, the limited depth of PU partitioning, the coding efficiency is still not sufficient to cope with the ever increasing demands for storage and transmission of video content.
SUMMARY
In light of the previously described problems, there exists a need for an apparatus and method, in which a more flexible block partitioning structure is used.
A binary tree structure is proposed for partitioning a unit into multiple smaller units such as partitioning a slice into CTUs, a CTU into CUs, a CU into PUs,  or a CU into TUs, and so on.
The binary tree structure can be combined with quadtree structure, which is a quadtree plus binary tree (QTBT) structure. In the QTBT structure, the root unit is firstly partitioned by a quadtree structure, then the leaf nodes of the quadtree is further partitioned by a binary tree structure. Some parameters for restriction of the quadtree and binary tree can be defined in high level such as in SPS.
BRIEF DESCRIPTION OF DRAWINGS
The invention can be more fully understood by reading the subsequent detailed description and examples with references made to the accompanying drawings, wherein:
Fig. 1 illustrates the subdivision of a CTU into CUs and TUs (left) and its corresponding quadtree (right) in HEVC.
Fig. 2 illustrates the types for splitting a CU into PUs in HEVC.
Fig. 3 illustrates the possible splitting types in the proposed binary tree.
Fig. 4 illustrates an example of block partitioning (left) and its corresponding binary tree (right) .
Fig. 5 illustrates an example of block partitioning (left) and its corresponding quadtree plus binary tree (right) .
DETAILED DESCRIPTION
The following description is of the best-contemplated mode of carrying out the invention. This description is made for the purpose of illustrating the general principles of the invention and should not be taken in a limiting sense. The scope of the invention is best determined by reference to the appended claims.
A binary tree block partitioning structure is proposed. In the proposed binary tree partitioning structure, a block can be recursively split into two smaller blocks. There are kinds of splitting types as shown in Fig. 3. The most efficient and simplest ones are the symmetric horizontal and vertical split as shown in the top two splitting types in Fig. 3. Therefore, as one embodiment, we only use these two splitting types. For a given block of size M×N, a flag signals whether it is split into two smaller blocks. If yes, another syntax element is signaled to indicate which  splitting type is used. If the horizontal splitting is used then it is split into two blocks of size M×N/2, otherwise if the vertical splitting is used then it is split into two blocks of size M/2×N. The binary tree splitting process can be iterated until the size (width or height) for a splitting block reaches a minimum allowed block size (width or height) that can be defined in high level syntax such as SPS. Since the binary tree has two splitting types horizontal and vertical, so the minimum allowed block width and height should be both indicated. Not horizontal splitting is implicit when splitting would result in a block height smaller than the indicated minimum. Not vertical splitting is implicit when splitting would result in a block width smaller than the indicated minimum. Fig. 4 illustrates an example of block partitioning (left) and its corresponding binary tree (right) . In each splitting (i.e., non-leaf) node of the binary tree, one flag indicates which splitting type (horizontal or vertical) is used, 0 indicates horizontal splitting and 1 indicates vertical splitting.
The proposed binary tree structure can be used for partitioning a block into multiple smaller blocks such as partitioning a slice into CTUs, a CTU into CUs, a CU into PUs, or a CU into TUs, and so on. As one embodiment, we use the binary tree for partitioning a CTU into CUs, i.e., the root node of the binary tree is a CTU and the leaf node of the binary tree is CU, the leaf nodes are further processed by prediction and transform coding. And for simplification as another embodiment there is no further partitioning from CU to PU or from CU to TU. That means CU equal to PU equal to TU, therefore, it is also to say that the leaf node of the binary tree is the basic unit for prediction and transform coding.
Binary tree structure is more flexible than quadtree structure, since much more partition shapes can be supported which is also the source of coding efficiency improvement. However, the encoding complexity will also increase in order to select the best partition shape. In order to balance the complexity and coding efficiency, it is proposed to combine the quadtree and binary tree structure, which is called as quadtree plus binary tree (QTBT) structure. In the proposed QTBT structure, a block is firstly partitioned by a quadtree structure, the quadtree splitting can be iterated until the size for a splitting block reaches the minimum allowed quadtree leaf node size. If the leaf quadtree block is not larger than the maximum allowed binary tree root node size, it can be further partitioned by a binary tree structure, the binary tree splitting can be iterated until the size (width or height) for a splitting block reaches the  minimum allowed binary tree leaf node size (width or height) or the binary tree depth reaches the maximum allowed binary tree depth. In the QTBT structure, the minimum allowed quadtree leaf node size, the maximum allowed binary tree root node size, the minimum allowed binary tree leaf node width and height, and the maximum allowed binary tree depth can be indicated in the high level syntax such as in SPS. Fig. 5 illustrates an example of block partitioning (left) and its corresponding QTBT (right) . The solid lines indicate quadtree splitting and dotted lines indicate binary tree splitting. In each splitting (i.e., non-leaf) node of the binary tree, one flag indicates which splitting type (horizontal or vertical) is used, 0 indicates horizontal splitting and 1 indicates vertical splitting.
The proposed QTBT structure can be used for partitioning a block into multiple smaller blocks such as partitioning a slice into CTUs, a CTU into CUs, a CU into PUs, or a CU into TUs, and so on. As one embodiment, we use the QTBT for partitioning a CTU into CUs, i.e., the root node of the QTBT is a CTU which is partitioned into multiple CUs by a QTBT structure, and the CUs are further processed by prediction and transform coding. And for simplification as another embodiment there is no further partitioning from CU to PU or from CU to TU. That means CU equal to PU equal to TU, therefore, it is also to say that the leaf node of the QTBT structure is the basic unit for prediction and transform.
For the proposed QTBT structure, we can take a specific example here. We have a CTU with size 128×128, and the allowed quadtree leaf node size equal to 16×16, the maximum allowed binary tree root node size equal to 64×64, the minimum allowed binary tree leaf node width and height both equal to 4, and the maximum allowed binary tree depth equal to 4. Firstly, the CTU is partitioned by a quadtree structure and the leaf quadtree unit may have size from 16×16 (minimum allowed quadtree leaf node size) to 128×128 (equal to CTU size, i.e., no split) , if the leaf quadtree unit is 128×128 it cannot be further split by binary tree since the size exceeds the maximum allowed binary tree root node size 64×64, otherwise the leaf quadtree unit can be further split by binary tree, the leaf quadtree unit which is also the root binary tree unit has binary tree depth as 0. When the binary tree depth reaches 4 (the indicated maximum) , not splitting is implicit, when the binary tree node has width equal to 4, not horizontal splitting is implicit, and when the binary tree node has height equal to 4, not vertical splitting is implicit. The leaf nodes of the QTBT are  further processed by prediction (intrapicture or interpicture) and transform coding.
The proposed tree structure is applied separately to luma and chroma for I slice, and applied simultaneously to both luma and chroma (except when certain minimum sizes are reached for chroma) for P and B slice. That is to say that, in I slice, the luma CTB has its QTBT-structured block partitioning, and the two chroma CTBs has another QTBT-structured block partitioning, wherein as another embodiment, the two chroma CTBs can also have their own QTBT-structured block partitionings.
The methods described above can be used in a video encoder as well as in a video decoder. Embodiments of the methods according to the present invention as described above may be implemented in various hardware, software codes, or a combination of both. For example, an embodiment of the present invention can be a circuit integrated into a video compression chip or program codes integrated into video compression software to perform the processing described herein. An embodiment of the present invention may also be program codes to be executed on a Digital Signal Processor (DSP) to perform the processing described herein. The invention may also involve a number of functions to be performed by a computer processor, a digital signal processor, a microprocessor, or field programmable gate array (FPGA) . These processors can be configured to perform particular tasks according to the invention, by executing machine-readable software code or firmware code that defines the particular methods embodied by the invention. The software code or firmware codes may be developed in different programming languages and different format or style. The software code may also be compiled for different target platform. However, different code formats, styles and languages of software codes and other means of configuring code to perform the tasks in accordance with the invention will not depart from the spirit and scope of the invention.
The invention may be embodied in other specific forms without departing from its spirit or essential characteristics. The described examples are to be considered in all respects only as illustrative and not restrictive. To the contrary, it is intended to cover various modifications and similar arrangements (as would be apparent to those skilled in the art) . Therefore, the scope of the appended claims should be accorded the broadest interpretation so as to encompass all such modifications and similar arrangements.

Claims (19)

  1. A video or image coding method that includes a binary tree block partitioning structure.
  2. The method as claimed in claim 1, wherein a block can be recursively partitioned into two smaller blocks until the size for a partitioning block reaches a minimum allowed size.
  3. The method as claimed in claim 2, wherein there are kinds of splitting types to split a block into two smaller blocks as shown in Fig. 3.
  4. The method as claimed in method 2, there are two splitting types to split a block into two smaller blocks which are symmetric horizontal splitting and symmetric vertical splitting as shown in Fig. 4.
  5. The method as claimed in claim 2, for a given block, a flag signals whether it is split into two smaller blocks, if yes, then another syntax element signals which splitting type is used.
  6. The method as claimed in claim 4 and claim 2, for a given block of size M×N, a flag signals whether it is split into two smaller blocks, if yes, then another flag signals which splitting type (horizontal or vertical) is used. If the horizontal splitting is used it is split into two blocks of size M×N/2, otherwise if the vertical splitting is used it is split into two blocks of size M/2×N.
  7. The method as claimed in claim 5-6, wherein not horizontal splitting is implicit when the height of the block reaches a minimum allowed height, not vertical splitting is implicit when the width of the block reaches a minimum allowed width.
  8. The method as claimed in claim 7, wherein the minimum allowed height and width are defined in high level syntax such as in SPS, PPS, slice header and so on.
  9. The method as claimed in claim 2 can be used for partitioning a CTU into CUs, i.e., the root node of the binary tree is CTU, and the leaf node of the binary tree is CU.
  10. The method as claimed in claim 9, wherein the CU cannot be further partitioned for prediction and transform. i.e., the CU equal to PU equal to TU. It is also to say that the leaf node of the binary tree is a basic unit for prediction and transform.
  11. The method as claimed in claim 2 can be used for partitioning a slice into  CTUs, partitioning a CU into PUs, partitioning a CU into TUs, partitioning a PU into TUs and so on.
  12. The method as claimed in claim 1, wherein the binary tree is rooted from a leaf node of a quadtree, which is a quadtree plus binary tree (QTBT) structure.
  13. The method as claimed in claim 12, a block is firstly partitioned by a quadtree structure, the quadtree splitting can be iterated until the size for a splitting block reaches the minimum allowed quadtree leaf node size. If the leaf quadtree block is not larger than the maximum allowed binary tree root node size, it can be further partitioned by a binary tree structure, the binary tree splitting can be iterated until the size (width or height) for a splitting block reaches the minimum allowed binary tree leaf node size (width or height) or the binary tree depth reaches the maximum allowed binary tree depth.
  14. The method as claimed in claim 13, wherein the minimum allowed quadtree leaf node size, the maximum allowed binary tree root node size, the minimum allowed binary tree leaf node width and height, and the maximum allowed binary tree depth can be indicated in the high level syntax such as in SPS, PPS, slice header, and so on.
  15. The method as claimed in claim 12 can be used in partitioning a CTU into CUs. i.e., the root node of quadtree is CTU, which is partitioned into multiple CUs by the QTBT structure.
  16. The method as claimed in claim 15, wherein the CU cannot be further partitioned for prediction and transform. i.e., the CU equal to PU equal to TU.
  17. The method as claimed in claim 12 can be used for partitioning a slice into CTUs, partitioning a CU into PUs, partitioning a CU into TUs, partitioning a PU into TUs and so on.
  18. The method as claimed in claim 2 and 12 is used in luma and chroma separately in I slice.
  19. The method as claimed in claim 2 and 12 is used in each color component (Y, Cb and Cr) separately in I slice.
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BR112017011889A BR112017011889A8 (en) 2014-12-10 2015-12-09 VIDEO ENCODING METHOD USING BINARY TREE BLOCK PARTITIONING
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