Intra Prediction Weighting for Block-Size Adaptive Compression
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Solution Overview
Problem
Existing video coding technologies face challenges in achieving high compression ratios with minimal sacrifice in picture quality, particularly in video data transmission and storage scenarios with limited bandwidth or memory resources.
Innovation Solution
The method involves intra prediction processes that utilize scaling factors based on block dimensions and intra prediction modes to calculate weighted sums of reference sample values, with normalization techniques to enhance prediction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If video data is compressed to reduce data size for transmission or storage, then the quantity of data needed is decreased, but picture quality is sacrificed
Solution Approach 1:
The current block is divided into multiple subpartitions (e.g., two subpartitions), and different intra prediction modes are applied to different subpartitions. This segmentation allows more flexible and accurate prediction across different regions of the block, improving picture quality while maintaining compression efficiency.
Solution Approach 2:
Different intra prediction modes (e.g., planar mode for one subpartition, angular mode for another) are applied to different subpartitions based on local characteristics. This local quality approach ensures that each subpartition is predicted using the most appropriate mode, thereby improving overall picture quality without excessively increasing data size.
2Productivity
If traditional intra prediction methods are used, then processing complexity is low, but prediction accuracy and compression ratio are limited
Solution Approach 1:
The block is segmented into subpartitions with different prediction modes, which improves prediction accuracy and compression ratio. The segmentation is implemented through a systematic process that divides the block and applies appropriate modes to each subpartition, balancing improved productivity with manageable complexity.
Solution Approach 2:
The intra prediction process dynamically selects different prediction modes for different subpartitions based on their characteristics. This dynamic approach allows the system to adapt to local variations in the block, improving compression ratio while keeping processing complexity reasonable through efficient mode selection.
Data Source
AI summary
A method for intra prediction is provided, the method including: obtaining a predicted sample value for a sample of the block; obtaining a scaling factor value according to an intra prediction mode for the current coding block, and according to at least one of: a height of the current coding block, or a width of the current coding block, or a size of a subpartition of the current coding block; determining a first weight value based on the scaling factor value; determining a second weight value based on the scaling factor value; calculating an additional value as a weighted sum of a top reference sample value and a left reference sample value, by weighting the top reference sample value with the first weight and the left reference sample value with the second weight; and obtaining a modified predicted sample value according to the additional value and the predicted sample value.