Chroma Block Prediction Using Luma-Based Adaptive Filtering
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Solution Overview
Problem
High-resolution and high-quality image data requires efficient compression methods to reduce transmission and storage costs, and existing technologies struggle with accurate prediction of chroma blocks in image encoding/decoding processes.
Innovation Solution
The method involves predicting a chroma block using a reconstructed luma block, determining filter coefficients based on luma and chroma components, and performing prediction in sub-block units to enhance accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution and high-quality image data is transmitted or stored using existing methods, then image quality is maintained, but transmission and storage expenses increase
Solution Approach 1:
The patent applies parameter changes by deriving filter coefficients dynamically based on the correlation between luma and chroma components. The filter coefficients are adjusted according to the actual image characteristics (such as gradient values and activity levels) rather than using fixed coefficients, enabling adaptive compression that maintains high image quality while reducing data volume.
2Measurement precision
If chroma block prediction is performed using existing technologies, then encoding/decoding is achieved, but prediction accuracy is insufficient
Solution Approach 1:
The patent segments the chroma block prediction process into multiple stages: first dividing the chroma block into sub-blocks, then deriving filter coefficients for each sub-block based on local luma-chroma correlation. This segmentation allows the system to capture local variations in the correlation between luma and chroma components, significantly improving prediction accuracy while keeping each individual sub-block processing relatively simple.
Solution Approach 2:
The patent applies local quality by using different filter coefficients for different sub-blocks of the chroma block. Each sub-block's filter coefficients are derived based on the local characteristics of the corresponding luma and chroma regions, allowing the prediction process to adapt to local variations in image content and achieve higher accuracy in regions with different correlation patterns.
3Measurement precision
If filter coefficients are derived using sub-block units, then prediction accuracy improves, but computational complexity increases
Solution Approach 1:
The patent applies partial action by deriving filter coefficients for only certain sub-blocks based on local characteristics, rather than uniformly processing all sub-blocks with the same complexity. The system selectively applies detailed coefficient derivation where needed (in regions with high luma-chroma correlation) and uses simpler methods where appropriate, balancing accuracy improvement with computational efficiency.
Data Source
AI summary
An image encoding/decoding method according to the present invention comprises the steps of: deriving filter coefficients for prediction of a chroma block; and on the basis of the filter coefficients, deriving a prediction sample for the chroma block by filtering a plurality of luma reconstructed samples within a luma block corresponding to the chroma block.