Cross-Component Filtering for Video Block Reconstruction
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Solution Overview
Problem
Existing video coding technologies face challenges in efficiently reducing redundancy and improving coding efficiency, particularly in handling intra prediction and motion compensation across different video components.
Innovation Solution
The implementation of cross-component filtering (CCF) on block-level reconstruction, which applies filtering processes to reconstructed samples of one color component to improve the prediction and reconstruction of subsequent blocks, thereby enhancing coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional intra coding without cross-component filtering is used, then device complexity is low, but coding efficiency and prediction accuracy are insufficient
Solution Approach 1:
The patent merges the filtering operation with the existing intra prediction process by applying cross-component filtering to chroma blocks using luma reference samples. This integration allows the filtering to be performed as part of the standard prediction workflow, improving coding efficiency without requiring a completely separate complex system.
Solution Approach 2:
The patent introduces an intermediary filtering step that processes chroma blocks by referencing luma samples. This intermediary process (cross-component filtering) acts as a mediator between the luma prediction and the final chroma reconstruction, improving prediction accuracy through the filtering operation.
2Measurement precision
If cross-component filtering is applied to improve prediction accuracy, then coding efficiency improves, but processing time and computational load increase
Solution Approach 1:
The patent applies cross-component filtering locally to chroma blocks rather than the entire picture. The filtering is performed only where needed (in chroma blocks) and uses locally available luma reference samples, which reduces the overall processing time compared to applying filtering globally while maintaining improved prediction accuracy in the affected regions.
3Loss of substance
If filtering is applied to reduce redundancy in video data, then storage and bandwidth requirements are reduced, but computational complexity increases
Solution Approach 1:
The patent changes the approach to redundancy reduction by introducing cross-component filtering that operates on chroma blocks using luma reference samples. This parameter change in the filtering methodology allows for more effective redundancy reduction in chroma data while maintaining manageable computational complexity through the use of existing luma samples.
Data Source
AI summary
An apparatus includes processing circuitry that decodes prediction information of a current block in a current picture that is a part of a coded video sequence. The processing circuitry determines whether a cross component filtering (CCF) process is enabled for the current block based on one of a partitioning scheme, a prediction mode, a block width, a block height, transform coefficients, and quantization parameters. The processing circuitry generates filtered reconstruction samples of the current block by applying the CCF process on at least one of predicted samples, residual values, or reconstruction samples of the current block based on the CCF process being enabled. The filtered reconstruction samples of the current block are used for reconstruction of a subsequent block. The processing circuitry reconstructs the current block and the subsequent block based on the filtered reconstruction samples of the current block.