Rice Parameter Update for Video Coefficient Coding
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Solution Overview
Problem
Existing video coding techniques face inefficiencies in adapting to large coefficient values and transform skipping or bypass scenarios, particularly in coding coefficient levels for screen content and natural content, due to limitations in the Rice parameter update scheme of the HEVC standard.
Innovation Solution
The proposed solution involves updating the Rice parameter used for Golomb codes based on a variable increment determined by the absolute value of the coefficient level, allowing the parameter to increase up to a maximum value, and adjusting the parameter based on whether a transform is applied to the block, enabling faster adaptation to large coefficient values and improving computational efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the Rice parameter is updated using the HEVC standard scheme, then coding performance is maintained, but adaptation to large coefficient values is slow
Solution Approach 1:
The Rice parameter update mechanism is made dynamic by introducing multiple update modes (first mode with faster increment for large coefficients, second mode with standard increment for normal cases). The system adapts the parameter value dynamically based on the magnitude of coefficient values encountered during encoding, allowing rapid adaptation when needed while maintaining stability during normal operation.
Solution Approach 2:
The invention changes the Rice parameter values based on the absolute values of transform coefficients. When large coefficient values are detected, the parameter is increased more aggressively using a first update mode, whereas standard update modes are used for normal cases. This parameter adaptation enables the coding scheme to handle different coefficient distributions effectively.
2Productivity
If the Rice parameter update scheme is simplified, then computational efficiency improves, but handling of transform skipping and bypass scenarios deteriorates
Solution Approach 1:
Different Rice parameter update strategies are applied locally based on the coding scenario. For transform skipping and bypass scenarios, the invention uses specific update rules that account for the absence of transform coefficients or direct coefficient usage. For normal transformed blocks, standard update modes are applied. This localized adaptation ensures optimal performance for each specific coding case.
3Device complexity
If conditional operations are reduced, then device complexity decreases, but adaptation precision worsens
Solution Approach 1:
The invention uses simple increment operations instead of complex conditional logic. Rather than implementing multiple nested conditionals to determine parameter updates, the system applies straightforward increment rules that are computationally inexpensive. The precision is maintained through the mathematical relationship between coefficient magnitudes and parameter increments, rather than through complex decision trees.
Data Source
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AI summary
Techniques are described for updating a value of a Rice parameter used to define Golomb codes for coefficient level coding. The Golomb codes defined by the Rice parameter may be used to code a remaining absolute value of a coefficient level for at least one coefficient in a coefficient group (CG). According to the techniques, the value of the Rice parameter is updated based on a selection of a minimum of either a maximum value of the Rice parameter or a variable increment of the value of the Rice parameter. The variable increment is determined based on the value of the Rice parameter and an absolute value of the coefficient level for the current coefficient being coded. Techniques are also described for adjusting the value of the Rice parameter used to define Golomb codes for coefficient level coding based on whether a transform is applied to a transform block.