Intra Template Matching Search Regions for Accurate Block Prediction
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Solution Overview
Problem
The existing Intra Template Matching Prediction (Intra TMP) technology does not fully utilize reconstructed neighboring samples, leading to suboptimal candidate blocks and reduced prediction accuracy.
Innovation Solution
The proposed method involves determining a first template for a current coding block and separately searching fully reconstructed and/or to-be-determined reconstructed search regions to find block vectors, utilizing both reconstructed and unreconstructed samples for improved prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the existing Intra Template Matching Prediction search strategy is used, then the search process is simple, but the prediction accuracy is reduced due to limited valid reference information
Solution Approach 1:
The search region is segmented into multiple sub-regions (first search region, second search region, third search region) based on different template types. Each sub-region is searched separately to find block vectors, allowing the system to utilize different reference information sources (fully reconstructed samples, to-be-determined reconstructed samples, and unreconstructed samples) according to the specific template characteristics, thereby improving prediction accuracy without requiring a completely complex new search strategy.
Solution Approach 2:
The method performs preliminary classification of templates into different types before the actual block vector search. By determining the template type first and selecting the appropriate search region accordingly, the system prepares the search strategy in advance, avoiding unnecessary searches in inappropriate regions and improving both accuracy and efficiency.
2Measurement precision
If the search region is divided into multiple sub-regions for separate searching, then the prediction accuracy is improved, but the computational complexity increases
Solution Approach 1:
Different search regions are assigned different qualities or characteristics based on the template type. The first search region uses fully reconstructed samples, the second uses to-be-determined reconstructed samples, and the third uses unreconstructed samples. This local differentiation allows each region to contribute optimally to the prediction based on its specific properties, improving overall accuracy while maintaining reasonable computational efficiency.
Solution Approach 2:
The system performs partial searching by selecting only the necessary search region(s) based on template type, rather than exhaustively searching all possible regions. This partial action approach finds the optimal block vector using only the relevant reference information, improving efficiency while maintaining the accuracy benefits of region-specific searching.
Data Source
AI summary
Provided are a decoding method, an encoding method, a bitstream, a decoder, an encoder and a storage medium. The decoding method includes: determining a first template corresponding to a current coding block; determining a fully reconstructed search region and/or a to-be-determined reconstructed search region according to the first template, wherein the fully reconstructed search region comprises a reconstructed sample, and the to-be-determined reconstructed search region comprises a reconstructed sample and/or an unreconstructed sample; and separately searching the fully reconstructed search region and/or the to-be-determined reconstructed search region and determining one or more block vectors of the current coding block.