Image Encoding Coefficient Grouping and Scanning
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Solution Overview
Problem
The increasing demand for high-resolution and high-quality images, such as HD and UHD images, results in larger amounts of data, leading to higher costs for transmission and storage. Existing image encoding/decoding techniques are not efficient enough to handle these higher-resolution and higher-quality images effectively.
Innovation Solution
An image encoding method that generates a transform block by performing transform and quantization, groups coefficients into coefficient groups, scans the coefficients using diagonal, zigzag, or boundary scanning, and encodes the coefficients. This method allows for efficient encoding and decoding of images by optimizing the scanning and grouping of coefficients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution and high-quality image data is transmitted or stored using conventional methods, then image quality is improved, but transmission and storage costs increase
Solution Approach 1:
The image data is divided into multiple transform blocks, which are further grouped into coefficient groups. This segmentation allows for selective processing and encoding of different regions, reducing the overall data amount while preserving important image quality characteristics.
Solution Approach 2:
The patent extracts and processes transform coefficients separately from the original image data through transform and quantization operations. By working with these extracted coefficients rather than the full image data, the method reduces data volume while maintaining essential image information.
2Quantity of substance
If conventional image compression techniques are used, then data transmission and storage costs are reduced, but encoding/decoding efficiency is insufficient for high-resolution images
Solution Approach 1:
The patent segments the encoding process into distinct stages: transform, quantization, grouping into coefficient groups, and scanning. This segmented approach improves encoding efficiency by allowing optimized processing at each stage, particularly through the grouping and scanning operations that are specifically designed for high-resolution image data.
Solution Approach 2:
The patent employs dynamic scanning methods (diagonal, zigzag, or boundary scanning) that can be selected based on the characteristics of the transform block. This dynamic adaptation to different image regions and patterns enhances encoding efficiency for high-resolution images while maintaining flexibility.
3Quantity of substance
If transform and quantization are performed on image data, then image data is compressed, but the amount of bits required for encoding coefficients increases
Solution Approach 1:
The patent merges adjacent coefficients into coefficient groups, combining multiple individual coefficient encoding operations into a single grouped operation. This merging reduces the total number of encoding operations required and decreases the overall bit rate while maintaining the compressed representation.
Solution Approach 2:
The patent applies scanning and grouping operations selectively to different regions of the transform block based on their characteristics. By applying partial action only where needed rather than uniformly across the entire block, the method reduces the bit rate while maintaining effective compression.
Data Source
AI summary
The present invention relates to an image encoding/decoding method and apparatus. An image encoding method according to the present invention may comprise generating a transform block by performing at least one of transform and quantization; grouping at least one coefficient included in the transform block into at least one coefficient group (CG); scanning at least one coefficient included in the coefficient group; and encoding the at least one coefficient.