Template Matching Block Vector Prediction for Image Encoding
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Solution Overview
Problem
Current image encoding/decoding technologies face challenges in efficiently handling high-definition and ultra-high-definition images, particularly in predicting pixel values effectively across different block partitioning structures for luma and chroma components.
Innovation Solution
The proposed solution involves using a template matching block vector for predicting pixel values in image encoding/decoding. This method includes deriving a block vector and using it to predict a prediction block for the current block, with independent prediction mode information for luma and chroma components. The block vector can be stored in a motion information buffer and added to a candidate list for subsequent blocks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If template matching prediction is used for high-definition and ultra-high-definition images, then prediction accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent divides the template matching process into multiple stages: generating candidate block vectors from a limited set of reference blocks, filtering candidates based on similarity metrics, and performing detailed matching only on selected candidates. This segmentation reduces the overall computational complexity while maintaining prediction accuracy for high-definition and ultra-high-definition images.
Solution Approach 2:
The patent applies different prediction strategies to different regions and components: separate template matching for luma and chroma components when they have independent block partitioning structures, and selective application of matching algorithms based on local block characteristics. This local quality approach optimizes computational resources by applying complex processing only where necessary.
2Measurement precision
If independent block partitioning structures are used for luma and chroma components, then prediction precision is improved, but device complexity increases
Solution Approach 1:
The patent implements dynamic selection of prediction modes based on block characteristics: independent template matching for luma and chroma is applied selectively when both components have independent block partitioning structures, otherwise unified matching is used. This dynamic approach allows the system to adapt to different scenarios, improving prediction precision while avoiding unnecessary complexity.
3Productivity
If block vectors are stored in motion information buffer and added to candidate lists, then prediction efficiency is improved, but memory usage increases
Solution Approach 1:
The patent manages memory resources by storing block vectors in a motion information buffer with limited capacity, discarding older or less relevant candidates when the buffer is full, and recovering useful information by adding selected block vectors to candidate lists for subsequent blocks. This approach maintains prediction efficiency while controlling memory usage through selective retention and disposal of data.
Data Source
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AI summary
Disclosed herein are a method, an apparatus and a storage medium for image encoding/decoding. Methods for performing more accurate prediction are disclosed when performing prediction using a block vector. A block vector for a target block is derived by template matching, and a prediction block for the target block is determined based on the derived block vector. Various and detailed embodiments for a plurality of pieces of information used to derive a block vector, such as a search area, a block vector candidate list, a reference region, a buffer, and a tree type, are provided.