Selective Transform Image Coding for Lower Data and Memory Load
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The increasing demand for high-resolution and high-quality images leads to a significant increase in transmission and storage costs due to the large amount of information required, necessitating a more efficient image compression technique.
Innovation Solution
An image decoding method and device that utilize a selective transform based on a modified transform matrix with a modified basis vector, allowing for non-separable transforms to reduce data transfer and computational complexity, thereby increasing residual coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If high-resolution and high-quality images are transmitted or stored, then image quality is improved, but transmission cost and storage cost increase
Solution Approach 1:
The patent applies parameter changes by using different transform types (first transform type and second transform type) depending on the characteristics of the image block. By changing the transform parameters adaptively based on block characteristics, the system achieves better compression efficiency while maintaining high image quality, thus reducing the amount of data needed for transmission and storage.
2Productivity
If conventional transform methods are used for residual coding, then coding simplicity is maintained, but residual coding efficiency is insufficient
Solution Approach 1:
The patent implements dynamics by adaptively selecting between different transform types based on the characteristics of each block. The transform type is dynamically chosen according to block size, prediction mode, or other characteristics, allowing the system to optimize residual coding efficiency for different content types while maintaining manageable complexity through standardized transform definitions.
3Productivity
If non-separable transforms are used, then transform efficiency is improved, but computational complexity and memory load increase
Solution Approach 1:
The patent applies segmentation by dividing the transform process into separate first and second transform types that can be applied independently to different blocks. This segmentation allows the system to use computationally intensive transforms only where beneficial, while using simpler transforms elsewhere, thus improving overall transform efficiency without uniformly increasing computational complexity across the entire image.
Data Source
AI summary
A method for decoding an image by a decoding device according to the present invention comprises the steps of: deriving, from a bit stream, transform coefficients of a block to be decoded; deriving residual samples of the block to be decoded, on the basis of a selective transform of the transform coefficients; and generating a reconstructed picture on the basis of the residual samples of the block to be decoded and prediction samples of the block to be decoded, wherein the selective transform is performed on the basis of a modified transform matrix, the modified transform matrix comprises a matrix including a modified basis vector, and the modified basis vector contains a certain number of elements selected from N elements.