Template-Matched Block Prediction for High-Resolution Image Coding
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Solution Overview
Problem
Existing image encoding/decoding technologies face challenges in efficiently handling high-resolution and high-definition images, particularly in predicting pixel values and compressing data effectively.
Innovation Solution
The use of template matching block vectors for predicting block values, with independent prediction modes for luma and chroma components, and the inclusion of block vectors in motion information buffers for improved prediction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If template matching prediction is used for high-resolution images, then prediction accuracy is improved, but computational complexity increases
Solution Approach 1:
The current block is divided into multiple sub-blocks, and template matching is performed independently for each sub-block. This segmentation reduces the overall computational complexity while maintaining prediction accuracy, as each sub-block requires less computation than the entire block would require.
Solution Approach 2:
Template matching is applied selectively to regions where it provides the most benefit, rather than uniformly across the entire image. This partial application reduces computational load while maintaining prediction accuracy in critical areas.
2Measurement precision
If independent prediction modes are used for luma and chroma components, then prediction precision is improved, but encoding complexity increases
Solution Approach 1:
Different prediction modes are applied to different color components (luma and chroma) based on their specific characteristics. The luma component uses one prediction mode optimized for brightness information, while the chroma component uses another mode optimized for color information, achieving local optimization for each component's quality.
3Measurement precision
If block vectors are stored in motion information buffer, then prediction accuracy is improved, but memory requirements increase
Solution Approach 1:
Only the essential block vector information is extracted and stored in the motion information buffer, rather than storing complete motion information for all blocks. This selective extraction reduces memory requirements while maintaining the prediction accuracy needed for template matching.
Data Source
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.