Image Decoding Candidate List Generation for Inter Prediction
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Solution Overview
Problem
Existing image compression technologies face challenges in efficiently generating candidate lists for inter prediction, particularly in deriving motion information for temporal candidates and adding various candidates to these lists.
Innovation Solution
An image decoding method and device that generate a candidate list for a current block, derive motion information based on spatial, temporal, or derived candidates, and perform inter prediction using this motion information. The method involves determining top-right and bottom-left blocks adaptively based on block sizes and shapes, and selectively adding derived candidates to the list.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional inter prediction methods are used to generate candidate lists, then the encoding/decoding process is simpler, but the prediction accuracy is insufficient
Solution Approach 1:
The candidate list is segmented into multiple types (spatial candidates, temporal candidates, and derived candidates), with each type obtained through different methods. This segmentation allows the system to explore diverse motion information sources without overwhelming complexity, as each segment has a specific derivation approach
Solution Approach 2:
Derived candidates act as intermediaries between spatial and temporal candidates. They are obtained by adaptively combining motion information from spatial neighboring blocks and temporal neighboring blocks, serving as a bridge that leverages the strengths of both approaches while mitigating their individual limitations
2Reliability
If motion information from multiple sources is combined to derive candidates, then the reliability of inter prediction is improved, but the computational complexity increases
Solution Approach 1:
The method dynamically adapts the derivation process based on the availability of motion information from spatial and temporal neighboring blocks. The derivation adaptively adjusts which candidates to generate and how to combine motion information, allowing the system to optimize reliability while managing complexity based on actual scene conditions
Solution Approach 2:
The method changes parameters such as the number of candidates in the list and the derivation approach based on the availability and quality of motion information from different sources. By adjusting these parameters adaptively, the system improves prediction reliability without incurring excessive computational complexity in all cases
3Measurement precision
If a comprehensive candidate list with multiple candidate types is generated, then the prediction quality is enhanced, but the encoding overhead increases
Solution Approach 1:
The derived candidate derivation method serves multiple functions: it enhances prediction quality by providing additional motion information sources, maintains compatibility with existing spatial and temporal candidate methods, and adaptively adjusts to different scene types. This multi-functionality allows comprehensive prediction quality enhancement without proportionally increasing encoding overhead
Data Source
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AI summary
An image encoding/decoding method and device according to the present disclosure may generate a candidate list of a current block and perform inter prediction of the current block on the basis of motion information of any one of multiple candidates belonging to the candidate list. The multiple candidates may include at least one of spatial candidates, temporal candidates, or derived candidates.