Context Adaptive Entropy Coding for Non-Square Video Blocks
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Solution Overview
Problem
Existing video coding techniques face inefficiencies in coding residual transform coefficients of non-square blocks, particularly due to the complexity of mapping these coefficients into square blocks for entropy coding, which can lead to loss of correlation and increased complexity.
Innovation Solution
The proposed techniques involve selecting appropriate scanning orders, determining contexts for entropy coding of significant and last significant coefficient positions, and coding values of residual transform coefficients based on the block's dimensions, allowing for context-adaptive entropy coding that reduces complexity and improves compression efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If non-square blocks are mapped into square blocks for entropy coding, then existing video coding techniques can be used, but complexity increases and correlation is lost
Solution Approach 1:
The non-square block is segmented into multiple square sub-blocks for entropy coding. Each sub-block is processed independently using existing square-block entropy coding techniques, avoiding the need to map the entire non-square block into a square block while preserving local correlations within each sub-block.
Solution Approach 2:
The patent changes the processing dimension by working with multiple 2D square sub-blocks simultaneously rather than attempting to transform the 1D non-square block into a 2D square block. This dimensional approach preserves spatial correlations while enabling use of existing square-block coding techniques.
2Ease of manufacture
If non-square blocks are mapped into square blocks for entropy coding, then existing video coding techniques can be used, but correlation is lost
Solution Approach 1:
By segmenting the non-square block into multiple square sub-blocks, the patent preserves local correlations within each sub-block while using existing square-block techniques. The segmentation ensures that correlated coefficients remain within the same sub-block, minimizing information loss.
Solution Approach 2:
The patent applies different processing to different parts of the non-square block by dividing it into square sub-blocks. Each sub-block maintains its local correlation structure, allowing existing entropy coding techniques to work effectively on each local region while preserving overall information.
3Productivity
If context-adaptive entropy coding is applied to non-square blocks, then compression efficiency improves, but determining appropriate contexts becomes more complex
Solution Approach 1:
The patent segments the non-square block into square sub-blocks, allowing context-adaptive entropy coding to be applied to each sub-block independently. This segmentation simplifies context determination by restricting it to smaller, localized regions where correlation patterns are more consistent and easier to model.
Solution Approach 2:
The patent determines contexts locally within each square sub-block rather than for the entire non-square block. This local approach improves compression efficiency by adapting to local correlation patterns while reducing the overall complexity of context determination by breaking the problem into smaller, manageable pieces.
Data Source
AI summary
Disclosed are techniques for coding coefficients of a video block having a non-square shape defined by a width and a height, comprising coding one or more of x- and y-coordinates that indicate a position of a last non-zero coefficient within the block according to an associated scanning order, including coding each coordinate by determining one or more contexts used to code the coordinate based on one of the width and the height that corresponds to the coordinate, and coding the coordinate by performing a context adaptive entropy coding process based on the contexts. Also disclosed are techniques for coding information that identifies positions of non-zero coefficients within the block, including determining one or more contexts used to code the information based on one or more of the width and the height, and coding the information by performing a context adaptive entropy coding process based on the contexts.