Luma-Based Chroma Intra-Prediction Using Down-Sampled Samples
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Solution Overview
Problem
Conventional video encoding and decoding methods fail to effectively utilize inter-channel correlation for improved coding efficiency, particularly in intra-prediction processes involving luma and chroma components.
Innovation Solution
A luma-based chroma intra-prediction method that employs down-sampled luma samples derived from weighting, using a filter circuit with a weighting table to generate down-sampled luma samples and compute parameters for a linear model to predict chroma samples, thereby enhancing prediction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional block-based coding is used, then coding structure is simple, but inter-channel correlation is not utilized and coding efficiency is low
Solution Approach 1:
The patent introduces down-sampled luma samples as an intermediary to bridge the luma and chroma prediction processes. These down-sampled luma samples serve as a mediator that captures inter-channel correlation information and transfers it to the chroma prediction, enabling efficient utilization of inter-channel correlation without directly processing complex chroma data.
Solution Approach 2:
The patent changes the parameter space by using down-sampled luma samples instead of full-resolution luma samples for chroma prediction. This parameter change reduces the complexity of chroma prediction while maintaining coding efficiency, as the down-sampled luma samples preserve the essential correlation information needed for accurate chroma prediction.
2Measurement precision
If chroma prediction uses full-resolution luma samples, then prediction accuracy is high, but data size and processing complexity increase
Solution Approach 1:
The patent extracts only the essential information from full-resolution luma samples by down-sampling them. This extraction process removes redundant high-frequency information while preserving the critical low-frequency correlation patterns needed for chroma prediction, thereby reducing data size without significantly compromising prediction accuracy.
Solution Approach 2:
The patent applies partial action by using down-sampled luma samples that provide sufficient prediction information for chroma blocks. This partial approach uses only the necessary portion of luma sample data (the down-sampled version) rather than all available data, achieving adequate prediction accuracy with reduced data quantity.
3Productivity
If intra-prediction processes all color components separately, then processing is simple, but inter-channel correlation is lost
Solution Approach 1:
The patent merges the luma and chroma prediction processes by using down-sampled luma samples in the chroma prediction. This merging allows the chroma prediction to benefit from luma information, capturing inter-channel correlation between luma and chroma components while maintaining a unified prediction framework that improves coding efficiency.
Data Source
AI summary
A luma-based chroma intra-prediction method includes: applying, by a filter circuit with a first weighting table, weighting to reconstructed luma samples to generate a first down-sampled luma sample, wherein the reconstructed luma samples are external to a luma block; computing parameters of a linear model, wherein a pair of the first down-sampled luma sample and a reconstructed chroma sample that is external to a chroma block is involved in computing the parameters of the linear model; and determining a predicted value of a chroma sample included in the chroma block according to the linear model and a second down-sampled luma sample that is derived from the luma block.