Coding Unit Partition With Chroma-Correlated Intra Prediction
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Solution Overview
Problem
Conventional image encoding and decoding methods lack effective means to improve performance and efficiency, particularly in reducing block degradation and enhancing prediction accuracy through intra prediction using color component correlation.
Innovation Solution
An image encoding/decoding method that utilizes the correlation between color components to generate prediction blocks, applies correction settings based on the size and type of the current block and prediction mode, and compensates prediction blocks to enhance accuracy and reduce block degradation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image encoding and decoding methods are used, then the encoding process is simple, but prediction accuracy is low and block degradation occurs
Solution Approach 1:
The current block is divided into multiple prediction blocks, and different correction settings are applied to different regions. The correction setting is determined based on the size of the current block and the prediction mode, allowing selective correction in specific areas to improve prediction accuracy without uniformly increasing complexity across the entire block.
Solution Approach 2:
Different correction operations are applied to different regions of the prediction block based on local characteristics. The correction setting varies according to the size of the current block and the type of prediction mode, enabling targeted improvement of prediction accuracy in regions where it is most needed while maintaining simplicity in other areas.
2Reliability
If correction is applied to prediction blocks, then block degradation is reduced, but processing complexity increases
Solution Approach 1:
Correction is applied selectively rather than uniformly to the entire prediction block. The correction setting is determined based on specific conditions (size of current block and prediction mode), applying correction only where necessary to reduce block degradation while avoiding unnecessary processing in regions where correction is not needed.
Solution Approach 2:
The correction setting is dynamically determined based on parameters such as the size of the current block and the type of prediction mode. By changing the correction parameters according to these conditions, the system adapts the processing complexity to the actual needs of each block, improving block quality only when and where required.
3Productivity
If intra prediction using color component correlation is implemented, then encoding performance is improved, but computational requirements increase
Solution Approach 1:
The correction setting is determined in advance based on the size of the current block and the prediction mode before the actual correction operation is performed. This preliminary determination of correction parameters allows the system to prepare the necessary computational resources efficiently, improving encoding performance by avoiding redundant calculations during the actual correction process.
Data Source
AI summary
Disclosed is an image decoding method using the correlation between color components to perform into prediction of chrominance components. Here, the image decoding method using the correlation between color components to perform intra prediction of chrominance components comprises the steps of: checking image data and a prediction mode in a bitstream; generating a prediction block according to a reconstructed prediction mode; determining compensation settings according to the size of a current block and the reconstructed prediction mode; compensating the prediction block according to the determined compensation settings; and reconstructing the current block by adding reconstructed image data to the prediction block.