Cross-Component Dependency Reduction for Low-Latency Chroma Coding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing video coding standards face high latency issues due to cross-component dependencies in chroma residual scaling and cross-component linear model prediction, particularly in dual/separate tree structures, leading to inefficient processing of chroma samples.
Innovation Solution
Proposed methods to reduce cross-component dependency by deriving chroma residual scaling factors using reference samples from the current block in reference frames, intermediate luma prediction values, and motion vectors, rather than waiting for full luma block reconstruction, and applying these methods selectively based on coding modes and block types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If chroma residual scaling and CCLM prediction wait for full luma block reconstruction, then prediction accuracy is improved, but processing latency increases
Solution Approach 1:
The patent applies preliminary action by using intermediate luma prediction values and motion vectors from reference frames to derive chroma residual scaling factors and CCLM parameters before the full luma block reconstruction is complete. This allows chroma processing to proceed in parallel with luma reconstruction, reducing waiting time while maintaining acceptable prediction accuracy through the use of available reference data.
2Measurement precision
If cross-component dependency is maintained in dual/separate tree structures, then prediction quality is improved, but processing complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the chroma processing into independent segments that can be handled separately from luma reconstruction. By using motion vectors and intermediate prediction values, the chroma residual scaling and CCLM parameter derivation are segmented into operations that do not require waiting for complete luma block availability, thereby reducing processing complexity while maintaining prediction quality.
Solution Approach 2:
The patent uses motion vectors and intermediate luma prediction values as intermediaries to bridge the cross-component dependency. These intermediaries allow chroma processing to access necessary luma-related information without requiring full luma block reconstruction, thus reducing processing complexity while preserving the beneficial cross-component prediction quality.
3Measurement precision
If chroma processing uses neighboring luma samples, then prediction accuracy is improved, but processing speed decreases
Solution Approach 1:
The patent applies preliminary action by pre-deriving motion vectors and intermediate luma prediction values from reference frames before chroma processing. This allows the chroma residual scaling and CCLM operations to use these pre-computed values instead of waiting for neighboring luma samples to be fully reconstructed, thereby improving processing speed while maintaining prediction accuracy through the use of reference frame data.
Data Source
AI summary
A method for visual media processing, including: computing, during a conversion between a current video block of visual media data and a bitstream representation of the current video block, a cross-component linear model (CCLM) and/or a chroma residual scaling (CRS) factor for the current video block based, at least in part, on neighboring samples of a corresponding luma block which covers a top-left sample of a collocated luma block associated with the current video block, wherein one or more characteristics of the current video block are used for identifying the corresponding luma block.