Chroma Fusion Prediction Using Candidate Model Parameters
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Solution Overview
Problem
The existing chroma prediction mode in video coding standards like H.266/VVC's Enhanced Compression Model (ECM) does not fully utilize the advantages of cross-component prediction, leading to low encoding efficiency due to simplified model parameters.
Innovation Solution
Optimize the determination of model parameters in the cross-component prediction mode by constructing a parameter candidate list and inheriting model parameters for the chroma fusion mode, rather than calculating them, to improve prediction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the chroma fusion mode uses a simple model parameter for cross-component prediction, then the encoding complexity is reduced, but the prediction accuracy deteriorates
Solution Approach 1:
The patent changes the parameter selection strategy by introducing a parameter candidate list that contains multiple model parameters (e.g., different alpha and beta values). Instead of using a single fixed simple parameter, the encoder selects the most appropriate parameter from the candidate list based on the specific block characteristics, thereby improving prediction accuracy while maintaining manageable encoding complexity through selective parameter usage.
Solution Approach 2:
The patent introduces dynamic parameter selection where the model parameters are not fixed but are chosen adaptively from a candidate list based on local characteristics of the current block. This dynamic approach allows the system to adjust the complexity and accuracy of prediction locally, using simpler parameters where sufficient and more accurate parameters where needed, thus resolving the contradiction between overall complexity and local accuracy.
2Measurement precision
If multiple model parameters are provided for cross-component prediction in chroma fusion mode, then the prediction accuracy is improved, but the encoding complexity increases
Solution Approach 1:
The patent applies partial action by providing multiple model parameters only when and where they are needed, rather than universally. The parameter candidate list is constructed and used selectively based on the chroma fusion mode indication and specific block requirements. This allows the system to gain accuracy benefits in regions where multiple parameters help, while avoiding the full encoding complexity overhead in regions where simpler prediction suffices.
Data Source
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AI summary
Disclosed in the embodiments of the present application are a coding method, a decoding method, a code stream, a coder, a decoder and a storage medium. The decoding method comprises: 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. Thus, the prediction accuracy of the chroma fusion mode can be improved, such that the coding and decoding efficiency can be improved.