Transform Unit Subset Decoding with Adaptive Golomb-Rice Coding
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Solution Overview
Problem
The existing video coding standards, such as H.264/MPEG-4 AVC, face challenges in achieving high compression efficiency when coding residual coefficients for video data, particularly at high resolutions or frame rates, due to inefficiencies in representing and encoding chroma channels and residual data.
Innovation Solution
The proposed solution involves a method for encoding and decoding a subset of transform units in video data using context-adaptive binary arithmetic coding (CABAC) and Golomb-Rice coding, which optimizes the representation of residual coefficients by selecting appropriate contexts and using parameterized Golomb-Rice codes to minimize bit-stream size, leveraging the predominance of low-frequency information in video data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If conventional video coding standards (H.264/MPEG-4 AVC) are used to code residual coefficients, then the coding process is simple and widely compatible, but compression efficiency is insufficient especially at high resolutions and frame rates
Solution Approach 1:
The transform unit is divided into multiple sub-sets, with different coding methods applied to each subset. Low-frequency coefficients use Golomb-Rice coding while high-frequency coefficients use bypass coding, optimizing compression for each frequency region separately
Solution Approach 2:
Different coding strategies are applied to different regions of the transform unit based on local characteristics. The low-frequency sub-sets receive more sophisticated Golomb-Rice coding while high-frequency sub-sets use simpler bypass coding, matching the local energy distribution
2Loss of energy
If all transform units are encoded with high precision methods, then compression efficiency improves, but processing time and computational complexity increase significantly
Solution Approach 1:
Instead of applying complex Golomb-Rice coding to all coefficients, the method applies it only to low-frequency sub-sets where it provides the most benefit. High-frequency coefficients use simpler bypass coding, achieving partial optimization that balances compression gain with processing speed
Solution Approach 2:
The coding parameter (coding method) is changed based on the frequency characteristics of different sub-sets. Golomb-Rice parameter K is adapted for low-frequency regions while bypass coding is used for high-frequency regions, optimizing the trade-off between compression ratio and processing speed
Data Source
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AI summary
A method of decoding a transform unit (e.g., 400) of encoded video data using Golomb-Rice decoding is disclosed. Significant residual coefficients for a sub-set of the transform unit are determined. A predetermined Rice parameter for Golomb-Rice decoding of the subset of the transform unit is selected. The predetermined Rice parameter being offset from a zero setting when the determined number of significant residual coefficients is higher than a predetermined threshold. The subset of the transform unit is decoded using the predetermined Rice parameter as an initial parameter for the Golomb- Rice decoding.