Chroma Fusion Prediction Using Inherited Cross-Component Parameters
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Solution Overview
Problem
The existing video encoding technologies, particularly in the H.266/VVC Test Model (ECM), do not fully utilize the advantages of cross-component prediction in chroma fusion mode, leading to low encoding efficiency.
Innovation Solution
Implement a method where, when the weighted chroma fusion mode is used, a parameter candidate list is constructed to determine model parameters for the current block based on a cross-component prediction mode, allowing for inheritance of model parameters rather than calculation, thereby optimizing the determination of model parameters in the chroma fusion mode.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the weighted chroma fusion mode is used with simple model parameters, then the encoding complexity is reduced, but the prediction accuracy deteriorates
Solution Approach 1:
The patent pre-calculates and stores multiple sets of model parameters (first model parameters, second model parameters, third model parameters) for different prediction scenarios before actual encoding. When encoding, the encoder selects from these pre-prepared parameters based on the current block's characteristics, avoiding complex real-time calculations while maintaining high prediction accuracy through inheritance of optimized parameters from candidate blocks.
2Device complexity
If the chroma fusion merge mode is not used, then the encoding process is simpler, but the encoding efficiency deteriorates
Solution Approach 1:
The patent implements a chroma fusion merge mode that copies model parameters from candidate blocks (spatial or temporal neighbors) to the current block. Instead of recalculating parameters for every block, the encoder copies proven parameters from similar blocks, significantly improving encoding efficiency while maintaining quality through the selection of appropriate candidate blocks.
3Device complexity
If cross-component prediction is not fully utilized, then the model parameter complexity is reduced, but the encoding efficiency deteriorates
Solution Approach 1:
The patent dynamically adjusts the utilization of cross-component prediction based on the current block's characteristics. The encoder determines whether to use first model parameters (from luma-chroma correlation), second model parameters (from chroma-only prediction), or third model parameters (from candidate block inheritance) based on conditions such as block size, position, and local image characteristics, thereby optimizing encoding efficiency without excessive complexity.
Data Source
AI summary
A coding method, a decoding method and a storage medium are provided. The decoding method includes: decoding a code stream, and determining the value of first syntax identification information; if the first syntax identification information indicates that the current block uses a weighted chroma fusion mode, decoding the code stream, and determining the value of second syntax identification information; if the second syntax identification information indicates that the current block uses a chroma fusion export mode, decoding the code stream, and determining an index identification value of the current block; and constructing a candidate parameter list of the current block, and determining a model parameter of the current block according to the candidate parameter list and the index identification value, wherein the model parameter is used for determining a first predicted value, which is based on a cross-component prediction mode, of the current block.