Secondary Transform Coding for Low-Frequency Coefficient Compression
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality images leads to increased transmission and storage costs due to the higher amount of information required, necessitating a more efficient image compression technique.
Innovation Solution
An image coding method and apparatus utilizing a non-separable secondary transform (NSST) to enhance transform efficiency by decoding or encoding a transform index before transform coefficients, concentrating non-zero coefficients on low frequency components, and applying secondary transforms to improve coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement 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 extracts only the essential visual information by applying transform coding to convert image blocks into frequency domain representations. By focusing on and transmitting only the significant transform coefficients (those containing important visual information) while discarding or coarsely encoding less important coefficients, the system achieves high-quality reconstruction with reduced data量
Solution Approach 2:
The patent changes the representation parameters of image data by applying secondary transforms (such as NSST - Non-Separable Secondary Transform) to the transform coefficients. This parameter transformation concentrates the energy of the coefficients, allowing more efficient quantization and encoding while preserving visual quality, thus reducing the amount of data needed to represent the same image quality
2Quantity of substance
If transform coding is applied to compress image data, then data compression is improved, but transform efficiency needs enhancement
Solution Approach 1:
The patent applies a preliminary primary transform (such as DCT or DST) to image blocks before applying the secondary transform. This preliminary transformation begins the process of concentrating energy into fewer coefficients, making the subsequent secondary transform more effective and reducing the overall computational complexity compared to applying a single complex transform
Solution Approach 2:
The patent employs multiple transform types (different primary transforms and secondary transforms) that can be dynamically selected based on the characteristics of the image block (such as prediction mode, block size, or content properties). This dynamic adaptability allows the system to optimize transform efficiency for different types of content while maintaining high compression ratios
3Productivity
If secondary transform is applied to transform coefficients, then coding efficiency is improved, but processing complexity increases
Solution Approach 1:
The patent segments the transform process into two distinct stages: primary transform and secondary transform. Each stage uses relatively simple, well-defined transform operations. By dividing the complex transformation task into manageable segments, the system achieves high coding efficiency while keeping the implementation complexity of each individual transform low and manageable
Data Source
AI summary
An image information decoding method performed by means of a decoding device according to the present invention comprises the steps of: decoding a non-separable secondary transform (NSST) index from a bitstream if NSST is applied to a target block; decoding information relating to transform coefficients with respect to the target block from the bitstream on the basis of the decoded NSST index; and deriving the transform coefficients with respect to the target block on the basis of the decoded information relating to the transform coefficients, wherein the NSST index is decoded prior to the information relating to the transform coefficients with respect to the target block.