Template-Matched Block Grouping for Accurate Intra Video Prediction
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Solution Overview
Problem
Existing video encoding and decoding technologies using Intra Template Matching Prediction (Intra TMP) suffer from low prediction accuracy due to incomplete consideration in the coding process, leading to deviations in certain scenarios.
Innovation Solution
Construct a first list of candidate matching blocks based on template matching, group them into subgroups, determine an index value for each subgroup, and fuse matching blocks within the subgroup to improve prediction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If reconstructed pixels of the matching block are directly used as prediction pixels, then the encoding process is simple, but prediction accuracy deteriorates due to large deviations in some scenarios
Solution Approach 1:
The patent segments the candidate matching blocks into multiple subgroups based on their spatial positions or characteristics. Instead of using a single matching block, the system divides the candidates into subgroups (e.g., first candidate matching block subgroup, second candidate matching block subgroup) and selects from these segmented groups, allowing for more precise prediction while maintaining manageable complexity
Solution Approach 2:
The patent merges multiple candidate matching blocks into subgroups and combines their information through fusion prediction. By merging the characteristics of multiple blocks within a subgroup and using fusion prediction modes, the system achieves higher prediction accuracy than using a single block, while the grouping structure keeps the process organized and manageable
2Measurement precision
If multiple candidate matching blocks are considered through grouping and fusion, then prediction accuracy improves, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing candidate matching blocks into subgroups with specific organizational rules. This segmentation structure allows the system to handle multiple candidates systematically, improving prediction accuracy while maintaining clear process boundaries that manage complexity
Solution Approach 2:
The patent uses partial action by selecting only the necessary number of candidate matching blocks and subgroups based on actual needs. The system determines an index value to select from the subgroups, using only the essential information needed for accurate prediction rather than processing all possible candidates, thus balancing accuracy with complexity management
3Productivity
If an index value is determined for each candidate matching block subgroup, then the coding efficiency improves by reducing code rate, but the complexity of determining and managing these indices increases
Solution Approach 1:
The patent extracts the essential selection information by determining an index value for each candidate matching block subgroup. Instead of transmitting full information about all candidates, the system extracts and transmits only the index values (e.g., first index value, second index value) that identify the selected subgroups, significantly reducing the code rate while maintaining coding efficiency
Solution Approach 2:
The patent applies preliminary action by pre-determining the index values for candidate matching block subgroups before the actual prediction process. The index values are prepared in advance based on the grouped candidates, allowing for efficient encoding and decoding without complex real-time calculations, thus improving coding efficiency while managing complexity through pre-computation
Data Source
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AI summary
Disclosed in embodiments of the present application are an encoding/decoding method, a code stream, an encoder, a decoder, and a storage medium. The method comprises: constructing a first candidate matching block list of a current block on the basis of template matching; grouping the first candidate matching block list, determining at least two candidate matching block groups, and determining an index value of each candidate matching block group; an encoding end determining an index value of a first candidate matching block group corresponding to the current block, and writing the index value of the first candidate matching block group into a code stream; and a decoding end determining the first candidate matching block group according to the index value, performing fusion according to the first candidate matching block group, and determining a prediction block of the current block. Thus, a candidate matching block list is constructed and grouped, a first candidate matching block group is indicated according to an index value, and fusion prediction is performed by using the first candidate matching block group, so that the prediction accuracy can be improved, the code rate is reduced, the encoding and decoding efficiency can be improved, and the coding and decoding performance is improved.