Adaptive Cross-Component Filtering for Video Coding Efficiency
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Solution Overview
Problem
Cross-component filtering (CCF) in video coding technologies, such as AV1 and VVC, incurs increased bit overhead and storage space when applied to smooth areas of image frames, as it requires signaling the presence or absence of CCF for each block, which is inefficient for frames with large smooth areas.
Innovation Solution
An image processing method that obtains statistics information of a block and determines whether it satisfies a specific condition, disabling CCF if the condition is met, thereby reducing unnecessary signaling and processing in smooth areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If cross-component filtering is applied to all blocks in an image frame, then filtering quality is improved, but bit overhead and storage space increase significantly
Solution Approach 1:
The patent applies different filtering treatments to different regions of the image frame based on local characteristics. Smooth areas are identified and excluded from CCF processing, while non-smooth areas continue to receive filtering. This local differentiation maintains filtering quality where needed while reducing bit overhead in regions where filtering provides minimal benefit.
Solution Approach 2:
The patent changes the parameter of CCF application from a uniform global setting to a conditional local setting. By introducing statistics-based conditions (smoothness detection) that modify the CCF application parameter, the system adapts the filtering behavior to local image characteristics, reducing overall bit overhead while maintaining necessary filtering quality.
2Measurement precision
If cross-component filtering is signaled for each block, then filtering precision is improved, but processing complexity increases
Solution Approach 1:
The patent performs preliminary detection of smooth areas using statistics information before applying CCF. By pre-identifying regions where CCF is unnecessary, the system avoids the complexity of signaling and processing CCF for each block individually, while still maintaining precise filtering where it is truly needed.
3Stability of the object's composition
If cross-component filtering is applied uniformly, then filtering consistency is improved, but coding efficiency decreases
Solution Approach 1:
The patent transitions from a static uniform CCF application approach to a dynamic adaptive approach. The system dynamically determines whether to apply CCF to each block based on real-time statistics information about image smoothness. This dynamic adaptation improves coding efficiency by avoiding unnecessary processing in smooth areas while maintaining filtering consistency in regions that require it.
Data Source
AI summary
An image processing method includes obtaining statistics information of a block of an image frame, determining whether the statistics information satisfies a condition, and disabling cross-component filtering (CCF) for the block in response to the statistics information satisfying the condition.