Block-Based Video Prediction Using Partition Shape and Size
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Solution Overview
Problem
Existing image encoding/decoding technologies lack efficient methods for predicting pixel values based on the size and shape of blocks, which affects the accuracy and efficiency of high-resolution and high-definition image processing.
Innovation Solution
The proposed solution involves splitting a target block into multiple partition blocks and deriving a prediction mode for each partition block based on its size and shape, using Most Probable Mode (MPM) lists and reconstructed pixels as reference samples for prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a block is split into multiple partition blocks for prediction, then prediction accuracy is improved, but device complexity increases
Solution Approach 1:
The target block is divided into multiple partition blocks (e.g., first partition block, second partition block, third partition block, fourth partition block) based on the block split indicator. Each partition block is then processed with appropriate prediction modes, allowing for more precise local prediction while managing complexity through structured segmentation.
Solution Approach 2:
Different prediction modes are applied to different partition blocks based on their specific characteristics. For example, the first and second partition blocks may use one prediction mode while the third and fourth partition blocks use another mode, optimizing prediction accuracy for each local region rather than applying a uniform approach.
2Manufacturing precision
If prediction is performed on each partition block based on size and shape, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The prediction process considers the size and shape characteristics of each partition block individually. Blocks with different dimensions or aspect ratios receive tailored prediction treatments, improving precision for each local region while maintaining overall system manageability through the block split indicator framework.
Solution Approach 2:
Prediction parameters such as prediction mode, reference block selection, and processing order are adjusted based on the size and shape parameters of each partition block. This dynamic parameter adjustment improves prediction precision while avoiding the need for completely separate processing systems for different block types.
3Measurement precision
If multiple prediction modes are derived for different partition blocks, then prediction accuracy is improved, but loss of information increases
Solution Approach 1:
The block split indicator provides a compact representation that enables the derivation of multiple prediction modes for different partition blocks without requiring separate full-parameter sets for each block. This segmented approach reduces information loss by sharing common information while maintaining local specificity.
Solution Approach 2:
The block split indicator is derived in advance from the target block characteristics, enabling subsequent prediction mode derivation for multiple partition blocks. This preliminary action reduces information loss by pre-establishing the structural framework that guides subsequent prediction processes.
Data Source
AI summary
Disclosed herein are a video decoding method and apparatus and a video encoding method and apparatus. In video encoding and decoding, multiple partition blocks are generated by splitting a target block. A prediction mode is derived for at least a part of the multiple partition blocks, among the multiple partition blocks, and prediction is performed on the multiple partition blocks based on the derived prediction mode. When prediction is performed on the partition blocks, information related to the target block may be used, and information related to an additional partition block, which is predicted prior to the partition block, may be used.