Adaptive Filter Shape Selection in Video Block Coding
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Solution Overview
Problem
Conventional video coding techniques face limitations in improving performance, particularly in the application of fixed filter shapes, which can hinder the efficiency of filtering tools and coding performance.
Innovation Solution
A method is proposed where a filter shape is selected from a plurality of options for coding a video block, allowing for improved filtering performance by adapting to the specific characteristics of the video content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed filter shape is used for all samples, then the device complexity is reduced, but the filtering performance and coding efficiency deteriorate
Solution Approach 1:
The filter shape is made dynamic rather than fixed. The system automatically selects from multiple filter shapes (e.g., rectangular, diamond, cross) based on the characteristics of each sample or block, allowing the filter adapts to different visual content types such as edges, textures, or smooth regions, thereby improving filtering performance without manual intervention
Solution Approach 2:
The system changes the filter shape parameter according to the content characteristics. By varying the geometric parameters of the filter shape (size, orientation, form) based on block size, edge detection, or texture analysis, the system optimizes the balance between computational complexity and filtering effectiveness for each local region
2Productivity
If multiple filter shapes are used for different samples, then the coding efficiency is improved, but the device complexity increases
Solution Approach 1:
The video picture is segmented into smaller blocks or regions, and each segment is independently processed with an optimally selected filter shape. This segmentation allows the system to use multiple filter shapes simultaneously across different regions without overwhelming complexity, as each segment can be processed independently using its own optimal filter
Solution Approach 2:
The system implements a universal filter selection mechanism that can handle multiple filter shapes through a single integrated framework. The same processing pipeline accommodates different filter shapes (rectangular, diamond, cross, etc.) by selecting the appropriate shape based on pre-defined criteria, making the system multi-functional without requiring separate processing paths for each filter type
3Adaptability or versatility
If only one filter shape is used per color component, then the device complexity is minimized, but the adaptability to different video content deteriorates
Solution Approach 1:
Different filter shapes are applied to different local regions based on their specific characteristics. For example, rectangular filters for smooth regions, diamond filters for edge regions, or cross filters for texture regions. This local adaptation allows each region to receive the most appropriate filter treatment, significantly improving the system's adaptability to diverse video content
Solution Approach 2:
The system performs preliminary analysis of the video content (such as edge detection, texture analysis, or block characteristic evaluation) before selecting the filter shape. This preliminary action enables the system to pre-determine the optimal filter shape for each region, improving adaptability while keeping the actual filtering process straightforward and avoiding complex real-time calculations during filter application
Data Source
AI summary
Embodiments of the present disclosure provide a solution for video processing. A method for video processing comprises: determining, from a plurality of filter shapes during a conversion between a current video block of a video and a bitstream of the video, a first filter shape for coding a first sample of the current video block; and performing the conversion based on the first filter shape. Compared with the conventional solution, the proposed method can advantageously improve the performance of the filtering tool.