Coding Tree Block Partitioning for Boundary-Aware Video Decoding
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Solution Overview
Problem
Existing video encoding technologies struggle to efficiently process next-generation video contents with high spatial resolution and high frame rates, leading to increased memory storage and processing demands.
Innovation Solution
A method for adjusting block partitioning in the QTBT structure by parsing syntax elements to determine optimal partitioning into coding blocks using quad-tree, binary-tree, or ternary-tree structures, considering boundary conditions and valid regions, and signaling these decisions through Sequence Parameter Sets or Network Abstract Layer units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If block partitioning is performed using traditional methods, then processing simplicity is maintained, but compression performance deteriorates for next-generation video contents
Solution Approach 1:
The patent applies segmentation by dividing the block partitioning process into multiple hierarchical stages: first dividing a current block into two sub-blocks using binary-tree partitioning, then selectively dividing specific sub-blocks into four sub-sub-blocks using quad-tree partitioning. This multi-stage segmentation approach enables adaptive compression optimization without requiring complete reprocessing of all blocks, thus improving compression performance while controlling complexity.
Solution Approach 2:
The patent implements dynamic block partitioning by determining different partitioning strategies based on block characteristics and content requirements. The method dynamically selects between binary-tree and quad-tree partitioning modes, and adaptively chooses which sub-blocks to further partition based on local image features. This dynamic adaptation allows the system to optimize compression performance for each specific block while avoiding unnecessary processing complexity.
2Manufacturing precision
If high spatial resolution and high frame rate video contents are processed, then video quality is improved, but memory storage and processing demands increase
Solution Approach 1:
The patent applies local quality by performing selective quad-tree partitioning only on specific sub-blocks that require higher detail representation, rather than uniformly partitioning all blocks. The method identifies regions benefiting from finer partitioning and applies quad-tree division only there, while other regions use coarser binary-tree partitioning. This localized approach maintains high video quality in critical areas while reducing overall memory storage and processing demands.
3Loss of information
If block partitioning is optimized for compression performance, then the number of bits required for signaling is reduced, but processing complexity increases
Solution Approach 1:
The patent applies preliminary action by first performing binary-tree partitioning to create sub-blocks, then using the results of this first partitioning to inform subsequent quad-tree partitioning decisions. The method pre-establishes a partitioning framework through binary-tree division before applying more complex quad-tree partitioning only where needed. This preliminary structuring reduces the overall signaling complexity compared to directly applying optimal partitioning without a staged approach.
Data Source
AI summary
Disclosed are a method for decoding a video signal and an apparatus therefor. Specifically, a method for decoding an image may include: partitioning a current coding tree block into a plurality of coding blocks so that coding blocks partitioned from the current coding tree block are included in a current picture when the current coding tree block is out of a boundary of the current picture; parsing a first syntax element indicating whether a current coding tree block is partitioned into a plurality of subblocks when the current coding tree block satisfies a predetermined condition; and determining a split mode of the current coding tree block based on the syntax element.