Transform Coefficient Coding With Adaptive Context Mapping
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Solution Overview
Problem
Existing image and video codecs face challenges in maintaining low complexity while achieving high coding efficiency, especially with varying block sizes and additional data components like depth maps, which require multiple contexts and symbolization schemes to adapt to changing statistical properties of transform coefficients.
Innovation Solution
An apparatus and method that use a context-adaptive entropy decoder and encoder with parameterizable symbolization schemes to map transform coefficients into symbols, allowing for adaptive coding and decoding of transform coefficients across different block sizes and information types, using a common function for context dependency and symbolization parameter determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple contexts and symbolization schemes are used to adapt to changing statistical properties of transform coefficients, then coding efficiency is improved, but device complexity increases
Solution Approach 1:
The patent uses a single parameterizable symbolization scheme where the symbolization parameter is dynamically adjusted based on previously coded transform coefficients. This allows the system to adapt to changing statistical properties without requiring multiple fixed symbolization schemes, thereby maintaining coding efficiency while reducing the complexity of managing multiple schemes
Solution Approach 2:
The patent introduces dynamic adaptation by determining the symbolization parameter based on the statistics of previously coded transform coefficients. This dynamic adjustment allows the symbolization scheme to adapt to changing statistical properties during the coding process, achieving high coding efficiency without the need for multiple static contexts
2Productivity
If a parameterizable symbolization scheme with adaptive parameter determination is used, then compression rate is improved, but computational complexity increases
Solution Approach 1:
The patent changes the parameter of the symbolization scheme dynamically based on the statistics of previously coded transform coefficients. This parameter adaptation improves compression rate by better matching the symbolization to actual coefficient statistics, while the computational complexity is kept moderate by using a simple statistical analysis of previously coded coefficients
Solution Approach 2:
The symbolization parameter is determined automatically based on the statistics of previously coded transform coefficients, without requiring external control or complex manual adjustment. The system serves itself by adapting to its own coding history, improving compression while keeping the mechanism relatively simple
Data Source
AI summary
An idea used herein is to use the same function for the dependency of the context and the dependency of the symbolization parameter on previously coded/decoded transform coefficients. Using the same function—with varying function parameter—may even be used with respect to different transform block sizes and/or frequency portions of the transform blocks in case of the transform coefficients being spatially arranged in transform blocks. A further variant of this idea is to use the same function for the dependency of a symbolization parameter on previously coded/decoded transform coefficients for different sizes of the current transform coefficient's transform block, different information component types of the current transform coefficient's transform block and/or different frequency portions the current transform coefficient is located within the transform block.