Transform Unit Golomb-Rice Decoding for Residual Compression
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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 decoding transform units.
Innovation Solution
The method employs Golomb-Rice decoding for transform units, where a predetermined Rice parameter is selected based on the number of significant residual coefficients and quantization parameters to optimize the decoding process, allowing for efficient encoding and decoding of 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 straightforward, but compression efficiency is insufficient especially at high resolutions or frame rates
Solution Approach 1:
The patent applies parameter changes by dynamically selecting different Rice parameter values (K=0, K=1, K=2) for Golomb-Rice decoding based on the characteristics of residual coefficients and quantization parameters. This adaptive parameter selection optimizes compression efficiency for different video content types and resolutions without requiring completely new decoding architectures, thus improving compression while controlling complexity increases.
2Loss of energy
If fixed Rice parameter is used for Golomb-Rice decoding, then decoding is fast and simple, but compression efficiency is suboptimal for different types of video content
Solution Approach 1:
The patent implements preliminary action by pre-defining multiple Rice parameter values (K=0, K=1, K=2) and establishing selection criteria based on residual coefficient characteristics and quantization parameters before decoding begins. This allows the decoder to quickly select the appropriate parameter without complex real-time calculations, maintaining high decoding throughput while adapting to different content types.
Solution Approach 2:
The patent dynamically changes the Rice parameter value based on the statistical properties of residual coefficients and quantization parameters. By adapting the parameter to match the actual video content characteristics, the system achieves optimal compression efficiency for different content types while keeping the decoding process relatively simple through straightforward parameter selection logic.
3Loss of energy
If adaptive Rice parameter selection is implemented based on residual coefficient characteristics, then compression efficiency improves, but decoding complexity increases
Solution Approach 1:
The patent implements adaptive parameter changes by selecting from a limited set of predefined Rice parameter values (K=0, K=1, K=2) based on simple criteria involving residual coefficient characteristics and quantization parameters. This approach achieves improved compression efficiency while limiting complexity increases by using a small, manageable set of parameter options rather than continuous parameter optimization.
Data Source
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.