ALF Coefficient Derivation via Shared Inverse Matrix
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Solution Overview
Problem
The existing Adaptive Loop Filter (ALF) clipping index optimization process in video encoding systems is computationally intensive due to the repeated calculation of inverse matrices for each clipping setting candidate, leading to high computational complexity and inefficiency.
Innovation Solution
The process optimizes ALF clipping index optimization by sharing partial intermediate results between multiple clipping settings, reducing the number of multiplication operations required in Gaussian elimination, and calculating distortion differences instead of full distortion values to derive final ALF coefficients and clipping indices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the ALF clipping index optimization process calculates inverse matrices for each clipping setting candidate independently, then the accuracy of ALF coefficient derivation is improved, but the computational complexity increases significantly
Solution Approach 1:
The patent merges the calculation of inverse matrices for multiple clipping setting candidates into a single unified inverse matrix calculation. By combining the computations and sharing common intermediate results (such as the correlation matrix R and its inverse), the system maintains the accuracy of deriving ALF coefficients for multiple clipping settings while significantly reducing the overall computational complexity from calculating multiple separate inverse matrices to calculating one shared inverse matrix.
Solution Approach 2:
The patent performs preliminary calculation of the correlation matrix R and its inverse once, before proceeding to evaluate different clipping setting candidates. This preliminary action computes the common components that are needed for all clipping setting candidates, avoiding redundant calculations and reducing the total computational burden while maintaining derivation accuracy.
2Measurement precision
If the system calculates full distortion values for each clipping setting, then the optimization accuracy is improved, but the processing time increases
Solution Approach 1:
The patent extracts and computes only the essential distortion difference values rather than calculating full distortion metrics for all clipping settings. By focusing on the differences in distortion between candidates rather than absolute distortion values, the system reduces the computational time required while maintaining sufficient optimization accuracy to identify the best clipping setting.
Solution Approach 2:
The patent applies partial action by calculating distortion differences for a subset of clipping setting candidates rather than evaluating all possible settings exhaustively. This selective evaluation approach reduces processing time while maintaining optimization accuracy by identifying the best clipping setting among the most promising candidates.
Data Source
AI summary
Video encoding methods and apparatuses include receiving reconstructed video samples, determining an initial clipping setting for ALF coefficients, deriving clipping setting candidates from the initial clipping setting. ALF coefficients for the initial clipping setting and the clipping setting candidates are derived by solving inverse matrices, where partial intermediate results of solving ALF coefficients are shared by two or more clipping settings. A distortion value corresponds to the derived ALF coefficients for each clipping setting is computed, and final clipping indices for final ALF coefficients are determined according to the distortion values. ALF filtering is applied to the reconstructed video samples based on the final ALF coefficients and the final clipping indices.