Transform-Skipped Block Coding with Adaptive Context States
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Solution Overview
Problem
In High Efficiency Video Coding (HEVC), the encoding and decoding of transform skipped blocks are inefficient due to incorrect context probabilities, which disrupt the adaptive context model used for conventional transform blocks, leading to increased bit usage and compromised encoding/decoding performance.
Innovation Solution
The solution involves reusing the context model for transformed residual blocks for transform skipped blocks by changing the starting state in the context model, allowing the decoder/encoder to derive contexts for nonzero residual values, starting in a second state instead of the first, to better match the properties of transform skipped blocks, thus improving encoding and decoding efficiency without introducing new context models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the context model for transformed residual blocks is used for transform skipped blocks with the first state, then the encoding/decoding process is simplified, but the context probabilities become incorrect leading to increased bit usage and reduced compression efficiency
Solution Approach 1:
The patent applies different starting states of the context model based on the block type (transform skipped or conventional transform block). For transform skipped blocks, the context model starts in a second state that better matches their statistical properties, while conventional blocks continue to use the first state. This local differentiation optimizes context probabilities for each block type without increasing overall system complexity.
2Productivity
If the context model starting state is changed for transform skipped blocks, then compression efficiency is improved, but the context model adaptability across different block types may be compromised
Solution Approach 1:
The context model is made dynamic by selecting different starting states based on the block type. The model adapts its initial state according to whether the block is transform skipped or conventional, allowing optimal context probabilities for each case while maintaining a single unified context model structure that serves both block types effectively.
Data Source
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AI summary
Video encoder and decoder and methods therein for transform skipped encoding and decoding of blocks of pixels. The methods comprises a modified use of an existing context model associated with transform coefficients, for deriving contexts for a bitmask indicating which residual values (i.e. not transform coefficients), in a transform skipped residual block, that are greater than one. The methods are applicable to video coding schemes such as HEVC.