Reduced Inverse Transform Matrix for Image Coding Efficiency
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality images, such as HD and UHD images, leads to a significant increase in the amount of information or bits required for transmission and storage, resulting in higher transmission and storage costs.
Innovation Solution
The proposed method and apparatus enhance image coding efficiency by performing a reduced transform, which involves using a non-square reduced transform matrix to derive quantized transform coefficients and residual samples, thereby reducing the amount of data required for transmission and storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution and high-quality image data is transmitted or stored, then image quality is improved, but transmission cost and storage cost increase
Solution Approach 1:
The patent extracts and removes redundant information from image data through transform coding. By converting spatial domain data to frequency domain and eliminating coefficients below a threshold, the patent separates essential image information from redundant data, achieving compression while preserving quality.
Solution Approach 2:
The patent changes the representation parameters of image data by applying transform matrices (such as DCT or DST) to convert spatial domain coefficients to frequency domain coefficients. This parameter transformation enables efficient compression by concentrating energy in fewer coefficients.
2Quantity of substance
If conventional transform coding is used, then image data is compressed, but coding efficiency is limited
Solution Approach 1:
The patent introduces dynamic adaptability in transform coding by selecting different transform types (DST or DCT) and different transform block sizes based on prediction mode and block characteristics. This dynamic approach optimizes coding efficiency for different image content and prediction scenarios.
Solution Approach 2:
The patent changes transform parameters adaptively by selecting between different transform matrices and block sizes based on prediction mode, block size, and image characteristics. This parameter adaptation improves coding efficiency by matching the transform approach to the specific content being encoded.
3Quantity of substance
If transform coding is applied to residual data, then compression is achieved, but computational complexity increases
Solution Approach 1:
The patent applies transform coding selectively and partially by using reduced transform block sizes and conditional transform application based on prediction mode and block characteristics. This partial application reduces computational complexity while maintaining compression effectiveness for the most important residual components.
Solution Approach 2:
The patent segments the residual data processing by applying different transform types and block sizes to different regions or different prediction modes. This segmentation allows computationally simpler transforms to be used where appropriate, reducing overall complexity while maintaining compression performance.
Data Source
AI summary
An image decoding method performed by means of a decoding device according to the present invention comprises the steps of: deriving quantized transform coefficients with respect to a target block from a bitstream; performing inverse quantization with respect to the quantized transform coefficients with respect to the target block and deriving transform coefficients; deriving residual samples with respect to the target block on the basis of reduced inverse transform with respect to the transform coefficients; and generating a reconstructed picture on the basis of the residual samples with respect to the target block and prediction samples with respect to the target block. The reduced inverse transform is performed on the basis of a reduced inverse transform matrix. The reduced inverse transform matrix is a non-square matrix of which the number of columns is smaller than the number of rows.