Chroma Intra Prediction Filtering for Cross-Component Redundancy
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Solution Overview
Problem
Existing video coding techniques face limitations in accuracy and efficiency when encoding and decoding image and video data, particularly in reducing redundancy between color components.
Innovation Solution
Implementing chroma intra prediction with filtering, which involves obtaining chroma prediction values using spatial intra prediction modes and applying derived filter coefficients to enhance coding efficiency by reducing redundancy between color components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If chroma intra prediction with filtering is implemented, then coding efficiency is improved by reducing redundancy between color components, but device complexity increases due to additional filtering operations
Solution Approach 1:
The patent combines multiple prediction approaches (spatial intra prediction and cross-component prediction) and integrates filtering operations directly into the prediction process. By merging these operations, the system achieves better redundancy reduction while managing complexity through unified processing rather than separate stages.
Solution Approach 2:
The patent applies derived filter coefficients that are calculated based on prediction residuals and color component characteristics. By dynamically adjusting filter parameters based on the specific prediction mode and residual analysis, the system optimizes redundancy reduction without requiring complex fixed-structure filters.
2Measurement precision
If multiple prediction modes are used for chroma pixels, then prediction accuracy is improved, but processing time increases
Solution Approach 1:
The patent evaluates multiple prediction modes (spatial intra and cross-component) but applies filtering only when necessary based on residual analysis. This partial application of complex operations only when prediction accuracy benefits from them reduces overall processing time while maintaining high accuracy where needed.
Solution Approach 2:
The system uses prediction residuals as feedback to determine whether additional filtering operations are necessary. By analyzing the residual characteristics after initial prediction, the system dynamically decides whether to apply filtering, thereby avoiding unnecessary processing time while maintaining prediction accuracy.
Data Source
AI summary
Encoding using chroma intra prediction with filtering includes encoding a current block from a current frame, which includes obtaining a first chroma prediction value for a current chroma pixel using a current spatial intra prediction mode, obtaining a current luma prediction value for a current luma pixel collocated with the current chroma pixel, obtaining a second chroma prediction value for the current chroma pixel for the current chroma component by applying derived filter coefficients to the current luma prediction value, obtaining, as a third chroma prediction value for the current chroma pixel for the current chroma component, a weighted average of the first chroma prediction value and the second chroma prediction value, obtaining encoded chroma pixel data for the current chroma pixel by encoding the current chroma pixel using the third chroma prediction value, and including the encoded chroma pixel data in the encoded block data.