Transform Coefficient Escape Coding for Lower Bitstream Overhead
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Solution Overview
Problem
Current video encoding and decoding techniques introduce distortion and artifacts due to lossy compression, particularly in block-based coding, which affects the quality of decoded video data.
Innovation Solution
The use of a combination of Golomb-Rice and exponential Golomb coding for transform coefficient coding to reduce the number of bits needed to signal transform coefficients, thereby improving coding efficiency and limiting worst-case coding scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If lossy compression is used to reduce bitstream size, then the number of bits needed to signal transform coefficients is reduced, but distortion and artifacts are introduced into decoded video data
Solution Approach 1:
The patent applies parameter changes by switching between different coding methods (context-based coding vs. escape coding) depending on the coefficient level value. This dynamic parameter selection optimizes the balance between compression efficiency and decoding accuracy, reducing unnecessary bits while maintaining quality for significant coefficients.
Solution Approach 2:
The patent implements local quality by applying different coding strategies to different transform coefficients based on their significance. Context-based coding is used for coefficients within a certain range, while escape coding is used for larger values, creating a localized optimization approach that adapts to the specific characteristics of each coefficient.
2Productivity
If context-based coding is used for all transform coefficients, then coding efficiency is improved, but the worst-case coding scenarios consume excessive bits
Solution Approach 1:
The patent introduces dynamics by making the coding method adaptive rather than static. The encoder dynamically selects between context-based coding and escape coding based on the actual coefficient value, allowing the system to respond to different input conditions and avoid the worst-case bit consumption of pure context-based coding.
Solution Approach 2:
The patent applies segmentation by dividing the transform coefficient coding space into different regions. Coefficients with absolute values less than or equal to a threshold use context-based coding, while larger coefficients use escape coding with Golomb-Rice or exponential Golomb coding, creating segmented handling that optimizes overall bit usage.
3Measurement precision
If the number of coded bins is increased to improve precision, then more transform coefficient information is captured, but the complexity of the coding process increases
Solution Approach 1:
The patent uses escape codes as an intermediary mechanism for representing transform coefficients that fall outside the standard context-based coding range. This intermediary approach allows precise representation of large coefficient values without requiring an excessive number of coded bins, thereby maintaining precision while controlling complexity.
Data Source
AI summary
As part of bypass decoding syntax elements for a set of coefficients in response to reaching a maximum number of regular coded bins, a video decoder is configured to receive a prefix value for a transform coefficient; decode the prefix value using Golomb-Rice coding; in response to a length of the prefix value being equal to a threshold value, receive a suffix value for the transform coefficient; decode the suffix value using exponential Golomb coding; and determine a level value for the transform coefficient based on the decoded prefix value and the decoded suffix value.