Weighted Prediction Parameter Estimation for Video Compression
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Solution Overview
Problem
Existing video compression systems face challenges in improving compression efficiency, particularly in predicting image blocks to reduce the dynamic of prediction residual blocks, which affects data transmission and decoding processes.
Innovation Solution
The method involves estimating weighted prediction parameters using a first estimate and a second estimate based on a scaled reference image histogram, with the second estimate being used for predicting image blocks when histogram distortion criteria are met, and configuring parameters based on image components and bit-depth considerations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional prediction methods are used to predict image blocks, then the prediction process is simple and fast, but the prediction accuracy is insufficient and the dynamic range of prediction residual blocks is high
Solution Approach 1:
The patent performs preliminary histogram analysis and weighted prediction parameter estimation before the actual prediction process. By pre-calculating the weighted prediction parameters based on histogram distortion between current and reference images, the method prepares optimal prediction parameters in advance, thereby improving prediction accuracy without significantly increasing the complexity during the main prediction phase
Solution Approach 2:
The patent dynamically adjusts prediction parameters based on image content characteristics. By calculating histogram distortion and using it to determine weighted prediction parameters, the method adapts the prediction process to different image regions and content types, improving prediction accuracy while maintaining manageable complexity through selective parameter adjustment
2Measurement precision
If weighted prediction parameters are estimated using histogram distortion, then prediction accuracy improves, but computational complexity increases
Solution Approach 1:
The patent extracts only the essential histogram characteristics needed for prediction parameter estimation, rather than performing complete image analysis. By focusing on histogram distortion between current and reference images, the method isolates the key information required for accurate prediction while discarding redundant computational steps, thereby reducing overall computational power requirements
Solution Approach 2:
The patent applies histogram-based weighted prediction selectively rather than uniformly across all image blocks. By using histogram distortion to determine where weighted prediction parameters are most beneficial, the method performs partial action only where needed, improving prediction accuracy in critical regions while avoiding unnecessary computational overhead in other areas
3Productivity
If the prediction residual block dynamic is reduced, then compression efficiency improves, but more complex prediction methods are required
Solution Approach 1:
The patent uses histogram distortion as a feedback mechanism to guide the selection and adjustment of weighted prediction parameters. By continuously comparing the histogram characteristics of current and reference images, the method receives feedback on prediction accuracy and dynamically adjusts parameters to minimize residual block dynamic, thereby improving compression efficiency while keeping the complexity increase manageable through iterative optimization
Data Source
AI summary
Described are methods and apparatus for estimating weighted prediction parameters intended to be used for predicting an image block. A component of an image block of a video may be precited from a set of options that includes a first version of weighted prediction parameters, a refined version of the weighted prediction parameters, or no weighted prediction parameters, and the image block may be encoded.