Transform Coefficient Escape Coding With Golomb-Rice Prefix Switching
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Solution Overview
Problem
Current video encoding and decoding techniques introduce lossy compression artifacts, such as blockiness, due to transform and quantization processes, which affect the quality of decoded video data.
Innovation Solution
The use of a combination of Golomb-Rice and exponential Golomb coding for transform coefficient coding, where context decoding and encoding techniques are applied to reduce the number of bits needed to signal transform coefficients, and bypass decoding/encoding mechanisms are employed to manage coding scenarios efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If transform and quantization processes are used to compress video data, then the number of bits needed to signal residual data is reduced, but distortion is introduced into the decoded video data
Solution Approach 1:
The patent applies different coding strategies (context-based coding vs. bypass coding) based on the parameter of coefficient significance and position. By changing the coding parameter selection based on local video characteristics, the system achieves better compression efficiency while maintaining quality where needed.
Solution Approach 2:
The patent implements local quality by applying different coding methods to different regions of the transform coefficient data. Context-based coding is used for significant coefficients that require precision, while bypass coding is used for less significant coefficients where compression is prioritized. This local differentiation optimizes both quality and compression.
2Productivity
If context decoding is used for transform coefficients, then coding efficiency is improved, but the complexity of the decoding process increases
Solution Approach 1:
The patent segments the coefficient decoding process into two distinct paths: context-based decoding for significant coefficients and bypass decoding for less significant coefficients. This segmentation allows the system to achieve high coding efficiency where needed while keeping the overall complexity manageable through selective application of complex operations.
Solution Approach 2:
The patent applies partial action by using context-based coding only when necessary (for significant coefficients) rather than applying it universally. This selective approach achieves the benefits of context-based coding where needed while avoiding the complexity overhead in regions where it would provide minimal benefit.
3Measurement precision
If the number of coded bins is increased to signal more transform coefficient information, then coding precision is improved, but the number of bits required increases
Solution Approach 1:
The patent implements dynamic coding where the decoding strategy adapts based on the significance and position of each coefficient. The system dynamically switches between context-based and bypass coding modes, allowing precision to be applied dynamically where needed while reducing bit consumption in less critical regions.
Solution Approach 2:
The patent changes the coding parameter (mode of operation) based on the coefficient being encoded. By adjusting the coding parameter selection based on local characteristics, the system achieves high precision where required while maintaining overall compression efficiency through parameter adaptation.
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.