Cross Component Prediction for Chroma Encoding Efficiency
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Solution Overview
Problem
Existing image encoding/decoding methods lack efficiency in handling high-resolution and ultra-high-resolution images, particularly in effectively predicting chroma components.
Innovation Solution
The proposed method employs cross component prediction using a linear model, where a reference sample is constructed from pre-reconstructed samples adjacent to the current block, and a cross component prediction parameter is derived to improve encoding/decoding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional image encoding/decoding methods are used, then the processing is simpler, but the encoding/decoding efficiency is insufficient for high-resolution images
Solution Approach 1:
The patent performs preliminary reconstruction of chroma components using simplified methods before the main encoding/decoding process. By pre-reconstructing chroma components and storing them in a buffer, the system prepares data in advance that can be efficiently utilized during cross-component prediction, improving overall encoding/decoding efficiency without significantly increasing complexity
Solution Approach 2:
The patent introduces an intermediate buffer to store pre-reconstructed chroma components. This buffer acts as an intermediary between the initial chroma reconstruction and the final cross-component prediction process, allowing efficient data exchange and enabling the system to achieve better compression ratios without directly increasing the complexity of the main encoding path
2Measurement precision
If cross component prediction is not used, then the method is simpler, but the prediction accuracy of chroma components is insufficient
Solution Approach 1:
The patent changes the parameters used for chroma prediction by utilizing luma component information and previously reconstructed chroma components. Instead of using simple intra-prediction parameters, the system derives prediction parameters from the correlation between luma and chroma components, significantly improving prediction accuracy while maintaining manageable complexity through standardized parameter derivation processes
3Productivity
If high-resolution images are processed with conventional methods, then the image quality may be maintained, but the encoding/decoding efficiency decreases
Solution Approach 1:
The patent segments the image processing into distinct components: luma processing, chroma reconstruction, and cross-component prediction. By dividing the high-resolution image processing into these separate stages, each handling specific aspects with optimized algorithms, the system achieves both high processing speed and maintained image quality without requiring a single complex processing path
Data Source
AI summary
An image encoding/decoding method and device according to the present disclosure may configure a reference sample for a cross component prediction of a chroma component block, derive a cross component prediction parameter by using the reference sample, and make a cross component prediction of the chroma component block on the basis of the cross component prediction parameter and a luma component block corresponding to the chroma component block.