CCLM Parameter Selection for Video Intra Prediction
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Solution Overview
Problem
The existing H.266/VVC video coding standard faces increased complexity and reduced efficiency in encoding and decoding due to the need to determine the position of adjacent blocks for intra prediction using the Cross-component Linear Model Prediction (CCLM) mode.
Innovation Solution
The method involves determining multiple groups of CCLM parameters based on reference samples for a current block, selecting an optimal target parameter, and signaling a CCLM index value in the bitstream to indicate the target parameter for both the encoder and decoder, allowing for efficient intra prediction processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the position of adjacent blocks is determined for intra prediction using CCLM mode, then prediction accuracy is improved, but encoding and decoding complexity increases
Solution Approach 1:
The patent extracts only the essential CCLM parameters (scale factor and offset parameter) needed for prediction, rather than processing all possible adjacent block positions. By selecting and signaling only the most relevant parameters in the bitstream, the complexity of determining adjacent block positions is reduced while maintaining prediction accuracy.
Solution Approach 2:
The encoder performs preliminary selection of optimal CCLM parameters from multiple candidate groups before encoding. By pre-determining the best scale factor and offset parameter combinations and signaling their indices, the decoder can directly use these pre-selected parameters without performing complex searches, thus reducing decoding complexity while preserving prediction accuracy.
2Measurement precision
If multiple groups of CCLM parameters are determined using multiple groups of reference samples, then prediction precision is improved, but signaling complexity increases
Solution Approach 1:
Instead of signaling all multiple groups of CCLM parameters explicitly, the patent uses index values to reference and copy parameter groups. The encoder signals compact index values that point to pre-defined parameter groups, allowing the decoder to retrieve the actual parameter values without transmitting redundant information, thus reducing bitstream overhead while maintaining access to multiple parameter groups for high precision.
3Measurement precision
If CCLM mode is used for intra prediction, then chroma prediction accuracy is improved, but processing time increases
Solution Approach 1:
The optimal CCLM parameters are pre-calculated and selected during the encoding phase, with their indices stored in the bitstream. During decoding, the decoder simply retrieves the pre-selected parameters using the stored indices rather than performing time-consuming parameter selection and optimization, significantly reducing processing time while maintaining chroma prediction accuracy.
Data Source
AI summary
Disclosed are a colour component prediction method, encoder, decoder, and storage medium. When CCLM is used for a current block to determine its intra prediction value, the encoder determines multiple groups of corresponding CCLM parameters using multiple groups of reference samples of current block, determines a target CCLM parameter from multiple groups of CCLM parameters; sets a CCLM index value indicating to use the target CCLM parameter and signals same in bitstream; and determines intra prediction value of current block according to the target CCLM parameter. The decoder parses bitstream to determine a prediction mode parameter of current block, parses bitstream to determine a CCLM index value of current block when prediction mode parameter indicates intra prediction value of current block is determined using CCLM; determines target CCLM parameter according to the CCLM index value, and determines intra prediction value of current block according to the target CCLM parameter.