Inverse Reduced Secondary Transform for Image Coding Efficiency
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality images/videos, such as 4K and 8K ultra high definition, leads to higher data transmission and storage costs due to increased bit rates. Additionally, the need for efficient compression techniques is exacerbated by the rise of immersive media like virtual and augmented reality.
Innovation Solution
The proposed solution involves an image coding method and apparatus that enhance coding efficiency by using a reduced secondary transform (RST) and a transform set based on intra prediction modes. This method includes deriving quantized transform coefficients, performing dequantization, and applying an inverse RST using a selected transform kernel matrix from a predetermined set, which is determined by the intra prediction mode applied to the target block.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution and high-quality image/video data is transmitted or stored using conventional methods, then image quality is improved, but transmission cost and storage cost increase due to increased bit rate
Solution Approach 1:
The patent applies parameter changes by transforming image data from spatial domain to frequency domain using transform techniques (DCT, DST, or other transforms). This transformation changes the representation parameters of the data, allowing energy compaction where most important information is concentrated in fewer coefficients, thereby reducing the bit rate needed to represent the same image quality
Solution Approach 2:
The patent applies local quality by using different transform types (e.g., DCT for smooth regions, DST for edge regions) based on the local characteristics of image blocks. By adapting the transform method to local image properties, the coding efficiency is improved while maintaining high image quality with reduced bit rate
2Ease of manufacture
If conventional transform methods are used for image coding, then coding process is simple, but residual coding efficiency is insufficient
Solution Approach 1:
The patent applies dynamics by making the transform method adaptive rather than static. The transform type is dynamically selected based on intra prediction mode and block characteristics, allowing the system to optimize residual coding efficiency for different image content while maintaining a relatively simple overall coding structure
Solution Approach 2:
The patent applies segmentation by dividing the image into blocks and applying different transform methods to different blocks based on their characteristics. This block-based adaptive transform approach improves residual coding efficiency by treating different regions with appropriate transform methods while keeping the processing manageable
Data Source
AI summary
An image decoding method according to the present disclosure includes deriving transform coefficients through dequantization based on the quantized transform coefficients for the target block; deriving modified transform coefficients based on an inverse reduced secondary transform (RST) for the transform coefficients; deriving residual samples for the target block based on an inverse primary transform for the modified transform coefficients; and generating a reconstructed samples based on the residual samples, and prediction samples derived based on an intra prediction mode for the target block, wherein the inverse RST is performed based on a transform kernel matrix selected from a transform set including a plurality of transform kernel matrices, the transform set is determined based on a mapping relationship according to the intra prediction mode applied to the target block, and a plurality of intra prediction modes including the intra prediction mode of the target block are mapped to one transform set.