Video Encoding Merge Candidate List Construction
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Solution Overview
Problem
Current video encoding and decoding methods face inefficiencies in generating merging candidate lists, particularly in handling increasing video size, resolution, and frame rates, which affects coding efficiency and image quality.
Innovation Solution
The method involves generating spatial and temporal merging candidates, history-based motion vector prediction candidates, and pairwise average merging candidates to create a comprehensive merging candidate list, using template matching to reorder and combine candidates for improved encoding and decoding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional merging candidate list composition methods are used, then the encoding process is simpler, but coding efficiency deteriorates with increasing video size, resolution, and frame rate
Solution Approach 1:
The merging candidate list is segmented into multiple types of candidates (spatial, temporal, history-based, pairwise average) organized in a hierarchical structure. This segmentation allows the encoder to selectively compose candidates based on video characteristics, improving coding efficiency without requiring all candidates to be processed in every case.
Solution Approach 2:
Pairwise average merging candidates are generated in advance by averaging motion vectors from spatial and temporal neighbors before the actual merge mode decision. This preliminary action provides better initial candidates that improve prediction accuracy, especially for high-resolution and high-frame-rate videos where motion complexity is higher.
2Manufacturing precision
If more merging candidates are generated to improve prediction accuracy, then image quality improves, but the number of zero-motion vector candidates increases unnecessarily
Solution Approach 1:
The patent changes the parameter of motion vector composition by introducing pairwise average candidates that combine spatial and temporal motion information. This parameter change provides more diverse and accurate motion predictions, reducing the need for multiple zero-motion vector candidates while improving prediction accuracy.
3Manufacturing precision
If comprehensive merging candidate lists are constructed to handle high video size and resolution, then image quality improves, but hardware resource requirements increase
Solution Approach 1:
The merging candidate list composition is made dynamic by adapting the selection and composition of candidates based on video characteristics such as resolution, frame rate, and motion complexity. This dynamic approach ensures high image quality for complex videos while reducing hardware resource usage for simpler videos, as not all candidate types need to be fully processed in every case.
Data Source
AI summary
A method and an apparatus for encoding/decoding a video are provided. A method for decoding a video includes generating one or more spatial merging candidates, generating a temporal merging candidate. The method also includes generating one or more history-based motion vector prediction candidates. The method also includes generating a first merging candidate list based on the one or more spatial merging candidates, the temporal merging candidates, and the one or more history-based motion vector prediction candidates. The method also includes generating one or more pairwise average merging candidates when the first merging candidate list is not fulfilled with merging candidates. The method also includes generating a second merging candidate list based on the one or more pairwise average merging candidates and the first merging candidate list. The method also includes generating a prediction block of the current block based on the second merging candidate list.