Video Signal Transform Type Selection for Compression Efficiency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The increasing demand for high-resolution and high-quality video signals leads to increased data volumes, resulting in higher costs for transmission and storage, and existing image compression techniques are inadequate for efficiently handling stereographic image content.
Innovation Solution
A method and apparatus for hierarchically partitioning coding blocks and adaptively determining transform types and quantization parameters during encoding and decoding of video signals, allowing for selective inverse transforms and optimized quantization based on block characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image compression techniques are used for high-resolution video signals, then transmission and storage costs increase, but image quality and resolution requirements cannot be met
Solution Approach 1:
The image is divided into multiple blocks, and each block is processed independently with appropriate transform types selected based on local characteristics. This segmentation allows for more efficient compression by adapting to local image features while reducing overall data volume for transmission and storage.
Solution Approach 2:
The transform type is dynamically selected for each block based on its characteristics (e.g., DCT for smooth areas, DST for edge areas). This dynamic adaptation optimizes compression efficiency for each region, achieving high image quality while minimizing transmission and storage costs.
2Measurement precision
If high-resolution and stereographic image content are provided, then data volume increases, but compression efficiency is insufficient with existing techniques
Solution Approach 1:
Different transform types are applied to different blocks based on their local characteristics. Smooth blocks use DCT while edge blocks use DST, optimizing compression efficiency for each region and enabling effective handling of high-resolution and stereographic content.
Solution Approach 2:
The transform type parameter is changed based on block characteristics (variance, gradient). By adapting the transform parameter to local image features, the system achieves superior compression efficiency for high-resolution content compared to fixed transform methods.
3Ease of operation
If uniform transform processing is applied to all blocks, then processing simplicity is maintained, but encoding efficiency is reduced
Solution Approach 1:
The transform type is dynamically selected for each block based on its characteristics. Although this adds some complexity to the processing logic, it significantly improves encoding efficiency by adapting to local image features, achieving better compression ratios.
Solution Approach 2:
Each block automatically selects its own transform type based on its characteristics (variance, gradient calculations). This self-service approach allows the system to adapt to local features without requiring complex global optimization, balancing processing simplicity with encoding efficiency.
Data Source
AI summary
A method of processing video signal according to a present invention comprises determining a transform set for a current block comprising a plurality of transform type candidates, determining a transform type of the current block from the plurality of transform type candidates and performing an inverse transform for the current block based on the transform type of the current block.