Entropy Coding Parameter Updates for Transform Coefficient Levels
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Solution Overview
Problem
Existing video encoding and decoding methods face challenges in efficiently managing the abrupt variations of parameters used in entropy encoding and decoding of transformation coefficients, leading to suboptimal bit usage and image quality.
Innovation Solution
A method and apparatus for gradually updating parameters in entropy encoding and decoding of transformation coefficients, using a binarization method like Golomb-Rice or concatenate codes, by comparing the size of transformation coefficients with a critical value to determine parameter updates, thereby reducing bit amount and improving image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a parameter used in entropy encoding and decoding of transformation coefficient level is updated abruptly to adapt to changing data characteristics, then the encoding efficiency and image quality improve, but the parameter variation causes instability and suboptimal bit usage
Solution Approach 1:
The patent implements dynamic parameter adjustment by transitioning from fixed parameter encoding to adaptive parameter updating. The parameter is dynamically modified based on transformation coefficient characteristics (e.g., when coefficient magnitude exceeds a threshold), allowing the encoding system to adapt to changing data distributions while maintaining stability through controlled update conditions and gradual parameter transitions.
Solution Approach 2:
The patent applies parameter changes by modifying the parameter value used in entropy encoding based on the statistical characteristics of transformation coefficients. Specifically, the parameter is adjusted according to the magnitude and distribution of coefficients, enabling the encoding process to optimize bit usage for different types of video content while maintaining system stability through systematic update rules.
2Loss of energy
If the parameter is updated frequently to match the statistical characteristics of transformation coefficients, then the bit usage efficiency improves, but the complexity of the encoding process increases
Solution Approach 1:
The patent applies local quality by updating the parameter selectively based on local characteristics of transformation coefficients rather than uniformly across all data. The parameter is updated only when specific conditions are met (e.g., when coefficient magnitude exceeds a threshold), allowing the encoding process to adapt to local statistical variations while avoiding unnecessary updates that would increase complexity.
Solution Approach 2:
The patent implements partial action by performing parameter updates only when necessary, rather than continuously or uniformly. The update mechanism triggers selectively based on transformation coefficient characteristics, applying the parameter change only to the extent needed to improve encoding efficiency for the current data characteristics, thereby balancing efficiency gains with computational complexity.
3Adaptability or versatility
If a fixed parameter is used for entropy encoding of all transformation coefficients, then the encoding process remains simple and stable, but the adaptability to different image characteristics is reduced
Solution Approach 1:
The patent transitions from static to dynamic parameter usage, where the parameter adapts to different image characteristics through conditional updates based on transformation coefficient statistics. This dynamic approach enables the encoding process to handle diverse video content (different scenes, motions, textures) effectively while maintaining relative simplicity through rule-based update mechanisms rather than complex adaptive algorithms.
Data Source
AI summary
An video decoding apparatus including a parser which obtains bit strings corresponding to current transformation coefficient level information by arithmetic decoding a bitstream based on a context model; a parameter determiner which determines a current binarization parameter by updating or maintaining a previous binarization parameter based on a comparison of a threshold and a size of a previous transformation coefficient; a syntax element restorer which obtains the current transformation coefficient level information by performing de-binarization of the bit strings using the determined current binarization parameter and generates a size of a current transformation coefficient using the current transformation coefficient level information, wherein the current binarization parameter has a value equal to or smaller than a predetermined value.