Prediction Refinement Filter for Video Coding Residual Reduction
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Solution Overview
Problem
Current video coding techniques, such as those in the MPEG-4 AVC standard, face challenges in accurately predicting data, especially for high-frequency and textured content, leading to high residual errors due to limitations in prediction models and rate constraints, which affect coding efficiency.
Innovation Solution
The implementation of a prediction refinement filter that refines both intra and inter predictions using previously decoded and encoded data from neighboring regions, applied before the generation of the prediction residual, to enhance prediction accuracy and reduce residual errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional prediction models (intra/inter prediction) are used in MPEG-4 AVC standard, then coding efficiency is maintained within rate constraints, but prediction accuracy deteriorates for high-frequency and textured content leading to high residual errors
Solution Approach 1:
The patent applies a prediction refinement filter before residual calculation to pre-process the prediction data and remove artifacts. This preliminary action improves prediction accuracy by eliminating ringing effects and blocking artifacts before they propagate into residual errors, thereby reducing the information loss in the residual stream.
Solution Approach 2:
The prediction refinement filter acts as an intermediary component between the traditional prediction models and the residual calculation stage. It mediates by refining the prediction output using deblocking filter results and gradient calculations, thereby improving the quality of prediction data passed to the residual encoder without requiring changes to the core prediction algorithms.
2Measurement precision
If more sophisticated prediction modes are included to improve prediction accuracy, then prediction quality improves, but device complexity increases
Solution Approach 1:
The prediction refinement filter utilizes information already available in the coding loop (deblocking filter results, gradient calculations from neighboring blocks) to improve prediction accuracy. Rather than introducing entirely new prediction models, the system serves itself by reprocessing existing prediction outputs with refinement operations, thereby improving accuracy without proportionally increasing complexity.
Solution Approach 2:
The patent changes parameters of the existing prediction system by applying refinement operations controlled by flags and parameters that can be adaptively enabled or disabled. This allows the system to adjust prediction complexity dynamically based on content characteristics, improving accuracy when needed while maintaining lower complexity for simpler content.
3Loss of information
If prediction refinement filter is applied to improve prediction accuracy, then residual error reduces, but processing time increases
Solution Approach 1:
The prediction refinement filter is applied selectively rather than universally to all blocks. The system uses refinement flags and content-based decisions to apply the filter only where it provides significant benefit, thereby reducing residual errors in problematic areas while avoiding unnecessary processing time expenditure on blocks that don't require refinement.
Data Source
AI summary
There are provided methods and apparatus for video coding using prediction data refinement. An apparatus includes an encoder for encoding an image region of a picture. The encoder has a prediction refinement filter for refining at least one of an intra prediction and an inter prediction for the image region. The prediction refinement filter refines the inter prediction for the image region using at least one of previously decoded data and previously encoded data, the previously decoded data and the previously encoded data corresponding to pixel values in neighboring regions with respect to the image region.