Video Decoding Using YCbCr Correlation for Intra-Prediction
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Solution Overview
Problem
Existing video encoding/decoding methods struggle to accurately predict blocks based on the correlation of YCbCr components, particularly in non-square block shapes, which affects video compression efficiency.
Innovation Solution
A video decoding method and apparatus that predictively decode a target block by generating a prediction block for a chroma block using scaling and offset values determined from reconstructed neighboring information of both luma and chroma blocks, improving intra-prediction accuracy through Cross Component Linear Model (CCLM) based approaches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional intra-prediction methods are used for non-square blocks, then the encoding process is simple, but the prediction accuracy deteriorates
Solution Approach 1:
The patent changes the parameters used for prediction by introducing cross-component linear modeling that utilizes correlation between YCbCr components. Instead of using only luma components for prediction, the method employs chroma components to derive prediction values, fundamentally changing the parameter set from single-component to multi-component prediction.
Solution Approach 2:
The patent combines multiple components (luma and chroma) to create a composite prediction model. By merging information from different color components, the method achieves more accurate prediction for non-square blocks, similar to how composite materials combine different substances to achieve superior properties.
2Productivity
If YCbCr correlation is utilized for prediction, then the video compression efficiency is improved, but the computational complexity increases
Solution Approach 1:
The patent performs preliminary actions by pre-calculating the linear model parameters (scaling and offset values) based on reconstructed neighboring samples. These pre-computed parameters are then reused for prediction, reducing the computational burden during the actual encoding/decoding process while maintaining compression efficiency.
Solution Approach 2:
The method changes the approach by using linear modeling parameters derived from chroma components to predict luma values. This parameter transformation allows efficient computation through simple linear operations rather than complex multi-dimensional analysis, improving compression efficiency while controlling computational complexity.
3Measurement precision
If cross-component linear modeling is applied, then the intra-prediction accuracy is enhanced, but the processing time increases
Solution Approach 1:
The patent applies preliminary action by computing the linear model parameters in advance using reconstructed neighboring samples from the bitstream. Once these parameters (scaling factor and offset) are determined, they can be efficiently applied to generate prediction values, reducing the time required during actual processing while maintaining high prediction accuracy.
Solution Approach 2:
The patent substitutes complex mechanical-like processing with simpler mathematical operations. By replacing intricate prediction mechanisms with straightforward linear modeling equations, the method achieves enhanced accuracy while minimizing processing time through efficient computational substitution.
Data Source
AI summary
Disclosed is video encoding/decoding method and apparatus using a correlation of YCbCr. According to an aspect of the present disclosure, the video decoding method for predictively decoding a target block includes, receiving a bitstream and generating a residual block for a chroma block, generating reconstructed information in a luma block corresponding to the chroma block and reconstructed neighboring information about the luma block, generating reconstructed neighboring information about the chroma block, determining a scaling value and an offset value based on the reconstructed neighboring information about the chroma block and the reconstructed neighboring information about the luma block, generating a prediction block for the chroma block by applying the determined scaling value and offset value to the reconstructed information in the luma block, and generating a reconstructed block for the chroma block based on the residual block for the chroma block and the prediction block for the chroma block.