Chroma Prediction Weighting Using Cross-Component Luma Cues
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Solution Overview
Problem
Existing video coding technologies face challenges in efficiently predicting chroma blocks based on luma blocks, leading to suboptimal compression efficiency and quality.
Innovation Solution
Implement a cross-component prediction method that uses a weighted average of multiple chroma prediction blocks, derived from inter and intra prediction modes, with weights determined by neighboring block coding modes, and employs filter coefficients based on luma samples and merge candidates to enhance chroma prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional single-mode chroma prediction is used, then device complexity is low, but compression efficiency is insufficient
Solution Approach 1:
The patent applies dynamics by making the prediction mode adaptive rather than fixed. The chroma prediction dynamically selects between inter prediction mode and cross-component prediction mode based on the characteristics of neighboring blocks. This allows the system to optimize compression efficiency for different block types while maintaining manageable complexity through context-based mode selection.
Solution Approach 2:
The patent changes the prediction parameter by introducing a weighted average mechanism that combines multiple prediction blocks with different weights. Instead of using a single prediction mode, the system adjusts the contribution of each prediction mode (inter prediction vs. cross-component prediction) through weight parameters, allowing flexible optimization of compression efficiency.
2Measurement precision
If multiple chroma prediction blocks with weighted average are used, then prediction accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent applies local quality by making the prediction complexity adaptive to local block characteristics. Different neighboring blocks (top, left, top-left) are analyzed individually, and the prediction mode is selected based on local coding patterns. This ensures high prediction accuracy for blocks that benefit from complex prediction while avoiding unnecessary complexity for blocks where simpler prediction suffices.
Solution Approach 2:
The patent uses partial action by conditionally applying the weighted average of multiple prediction blocks only when beneficial. The system evaluates neighboring block characteristics and applies the complex weighted prediction mechanism selectively rather than universally, thus improving accuracy where needed while controlling overall computational complexity.
3Manufacturing precision
If cross-component prediction with luma filtering is applied, then chroma quality is enhanced, but processing overhead increases
Solution Approach 1:
The patent applies preliminary action by preparing the luma samples and filter coefficients in advance before performing cross-component prediction. The luma samples are filtered using pre-derived filter coefficients based on luma prediction and chroma prediction, so that when cross-component prediction is needed, the filtering work has already been done, reducing real-time processing overhead.
Solution Approach 2:
The patent uses luma samples as an intermediary to improve chroma prediction. Instead of directly predicting chroma from chroma references, the system uses luma information (which is already available from luma prediction) as an intermediate step to derive cross-component prediction blocks. This intermediary approach enhances chroma quality by leveraging the correlation between luma and chroma while reusing existing luma processing results.
Data Source
AI summary
In a method, a first chroma prediction block of a chroma block of a current block is determined based on an inter prediction mode. A second chroma prediction block of the chroma block of the current block is determined based on a cross-component prediction mode in which the second chroma prediction block is derived based on reconstructed luma samples of a luma block of the current block. A prediction block of the chroma block is determined as a weighted average of the first chroma prediction block of a plurality of chroma prediction blocks and the second chroma prediction block of the plurality of chroma prediction blocks. A first syntax element is encoded in a bitstream that indicates the chroma block of the current block is predicted by the weighted average of the plurality of chroma prediction blocks.