SAD, SATD, and SSTD Cost Functions for Video Block Coding
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Solution Overview
Problem
Conventional video coding techniques suffer from suboptimal coding efficiency, as they primarily rely on a single error metric for determining distortion between blocks, which limits the accuracy and quality of coding.
Innovation Solution
The proposed method utilizes at least two different error metrics to measure distortion between video blocks, refining coding data based on these metrics to improve coding quality and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single error metric is used to determine distortion between blocks, then the device complexity is reduced, but the measurement precision of distortion is insufficient
Solution Approach 1:
The patent combines multiple error metrics (SAD, SATD, SSTD) into a unified cost function that comprehensively evaluates distortion between video blocks. This merging of multiple measurement approaches enables more accurate distortion assessment while managing computational complexity through systematic integration of the metrics.
Solution Approach 2:
The patent changes the parameter of error measurement by introducing multiple error metrics instead of relying on a single metric. The cost function dynamically selects and combines different error metrics (sum of absolute differences, sum of absolute transformed differences, sum of squared transformed differences) based on coding conditions, thereby improving measurement precision without excessive complexity increase.
2Productivity
If conventional video coding techniques are used with single error metric, then the coding speed is maintained, but the coding efficiency is suboptimal
Solution Approach 1:
The patent introduces dynamic selection of error metrics based on coding conditions and block characteristics. The cost function adaptively chooses which error metrics to apply (SAD, SATD, SSTD) depending on the specific coding scenario, enabling more precise distortion measurement that improves coding efficiency while maintaining adaptability to different video content types.
Solution Approach 2:
The patent segments the distortion measurement process into multiple independent error metric calculations (SAD for luminance, SATD for transformed differences, SSTD for squared differences). Each metric addresses specific aspects of distortion, and their results are combined to provide comprehensive measurement, thereby improving coding efficiency through more accurate block evaluation.
Data Source
AI summary
Embodiments of the present disclosure provide a solution for video processing. A method for video processing is proposed. The method comprises: determining, during a conversion between a current video block of a video and a bitstream of the video, a cost based on at least two error metrics associated with two target blocks of the video, the cost indicting a degree of distortion between the two target blocks; refining coding data of the current video block based on the cost and the two target blocks; and performing the conversion based on the refined coding data. Compare with the conventional solution, the proposed method can advantageously improve the coding quality and the coding efficiency.