Video Prediction Blocks Using Multi-Mode Sub-Block Encoding
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality video images leads to higher data volumes, resulting in increased costs for transmission and storage, and existing video compression techniques are inadequate for efficiently encoding and decoding stereographic content.
Innovation Solution
A method and apparatus that combine multiple prediction modes, such as intra and inter prediction, to generate a final prediction block through weighted sum operations, allowing prediction in units of sub-blocks, and utilize a hierarchical partitioning structure for video encoding and decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional image compression techniques are used for high-resolution video, then transmission and storage costs increase, but image quality and resolution requirements cannot be met
Solution Approach 1:
The current block is divided into multiple sub-blocks, and different prediction modes are applied to different sub-blocks. This segmentation allows the encoder to select the most appropriate prediction mode for each sub-block, improving overall prediction accuracy and compression efficiency while meeting high image quality requirements.
Solution Approach 2:
The patent dynamically selects between intra prediction mode and inter prediction mode for different sub-blocks based on local characteristics. This dynamic adaptation enables the system to optimize prediction accuracy for each region, reducing residual energy and thereby lowering transmission and storage costs while maintaining high image quality.
2Measurement precision
If multiple prediction modes are combined for video encoding, then prediction accuracy improves, but computational complexity increases
Solution Approach 1:
By dividing the current block into sub-blocks and applying different prediction modes to each, the system achieves higher overall prediction accuracy. The segmentation allows complex multi-mode prediction to be applied selectively only where needed, rather than uniformly across the entire block, thus managing computational complexity.
Solution Approach 2:
Different prediction modes are applied to different sub-blocks based on their local characteristics. This local quality approach ensures that each sub-block receives the most appropriate prediction treatment, maximizing prediction accuracy locally while avoiding unnecessary computational complexity in regions where simpler modes suffice.
3Measurement precision
If prediction is performed in sub-block units, then prediction precision improves, but processing time increases
Solution Approach 1:
The current block is segmented into multiple sub-blocks to improve prediction precision by capturing local variations more accurately. However, the segmentation is performed with consideration for processing efficiency, using a reasonable number of sub-blocks that balances precision improvement with acceptable processing time.
Solution Approach 2:
Prediction is performed in sub-block units to achieve local precision, but the system optimizes the sub-block size and number to prevent excessive processing time. The local quality approach allows precision-critical regions to use finer sub-block segmentation while less critical regions use coarser segmentation, balancing overall processing time.
Data Source
AI summary
A method for decoding a video according to the present invention may comprise: generating a first prediction block for a current block based on a first prediction mode, generating a second prediction block for a current block based on a second prediction mode, and generating a final prediction block of the current block based on the first prediction block and the second prediction block.