Color-Component Intra Prediction for Image Coding Efficiency
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Solution Overview
Problem
Existing image encoding and decoding technologies lack efficient methods for deriving intra prediction modes and configuring reference pixels, particularly for different color components, leading to suboptimal performance in image processing systems.
Innovation Solution
An image encoding/decoding method and device that determines intra prediction modes based on color components, using prediction mode candidate groups classified into categories, and configures reference pixels with weighted or interpolation filters, allowing selective modification of prediction blocks based on coding information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional image encoding and decoding methods are used, then the system can process images, but the performance and efficiency of image processing are insufficient
Solution Approach 1:
The patent applies parameter changes by dynamically selecting intra prediction modes based on color component characteristics (luma vs. chroma). Different prediction mode candidate groups are configured for different color components, and the selection is adjusted according to block size, position, and other state information. This parameter-based adaptation resolves the contradiction by optimizing both processing efficiency and performance through targeted parameter adjustments rather than uniform processing.
Solution Approach 2:
The patent implements local quality by treating different color components (luma and chroma) and different block regions with distinct prediction strategies. Specifically, luma components use one set of prediction mode candidates while chroma components use another set. This localized optimization ensures that each region receives the most appropriate processing method, simultaneously improving overall efficiency and performance.
2Measurement precision
If intra prediction modes are not differentiated by color component, then the encoding process is simpler, but the accuracy and coding performance deteriorate
Solution Approach 1:
The patent applies segmentation by dividing the prediction mode selection process into distinct segments for different color components. Luma components are processed with one candidate group while chroma components use another. This segmentation increases prediction accuracy by component-specific optimization while managing complexity through systematic organization of the different processing paths.
Solution Approach 2:
The patent implements universality by creating a multi-functional prediction mode selection framework that handles both luma and chroma components through a unified decision-making process. The same apparatus and methodology are used for both color components, with automatic selection of appropriate candidate groups based on component type, thereby achieving high accuracy without proportionally increasing system complexity.
3Measurement precision
If all prediction modes are used for all blocks, then the prediction accuracy is maximized, but the coding overhead and processing complexity increase
Solution Approach 1:
The patent applies partial action by selecting only the necessary prediction mode candidate groups for each specific case rather than using all possible modes universally. Based on color component type, block size, and position, the system activates only the relevant candidate groups, achieving sufficient prediction accuracy while minimizing coding overhead by avoiding transmission and processing of unnecessary mode information.
Data Source
AI summary
Image encoding/decoding method and device according to the present invention enable deciding of an intra-screen prediction mode of a target block, generation of a prediction block of the target block on the basis of the intra-screen prediction mode, and correction of the generated prediction block.