Adaptive Coding Unit Shape Selection for High-Resolution Image Encoding
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Solution Overview
Problem
Existing image compression methods using uniform square coding units lead to image quality deterioration due to inefficiencies in high-resolution image encoding and decoding, particularly with the increasing demand for high-resolution images.
Innovation Solution
The method involves determining coding units based on block shape information, allowing for the use of transformation units of various shapes, which are adaptive to the image characteristics, enabling efficient encoding and decoding by performing inverse transformation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If uniform square coding units are used for image compression, then the encoding process is simple, but image quality deteriorates in high-resolution images
Solution Approach 1:
The image is divided into multiple coding units of different shapes (square, rectangular, triangular) rather than uniform squares. This segmentation allows the encoder to select appropriate shapes for different image regions, improving compression efficiency and image quality while maintaining manageable encoding complexity through systematic shape classification and selection mechanisms
Solution Approach 2:
Different coding unit shapes are applied to different regions of the image based on local characteristics. The encoder selects coding unit shapes adaptively for each region, allowing optimal representation for various image content types (e.g., smooth regions, edges, textures) thereby improving overall image quality without requiring complex encoding throughout the entire image
2Manufacturing precision
If various shaped transformation units are used to adapt to image characteristics, then image quality improves, but the encoding and decoding complexity increases
Solution Approach 1:
The coding unit shape is made dynamic and adaptable rather than fixed. The encoder selects from multiple predefined shapes (square, rectangular, triangular) based on image characteristics, allowing the system to adapt to different content types while maintaining controlled complexity through aĉé set of shape options and systematic selection criteria
Solution Approach 2:
The shape parameter of coding units is changed adaptively based on image characteristics. By modifying the shape parameter (square, rectangular, triangular) according to local image features, the system achieves better compression performance and image quality while managing complexity through parameter-based shape selection rather than arbitrary shape variations
Data Source
AI summary
Provided is a method of decoding an image, the method including: determining at least one coding unit for splitting an image, based on block shape information of a current coding unit; determining at least one transformation unit, based on a shape of the current coding unit included in the at least one coding unit; and decoding the image by performing inverse transformation based on the at least one transformation unit, wherein the block shape information indicates whether the current coding unit is a square shape or a non-square shape. Also, provided is an encoding method corresponding to the decoding method. In addition, provided is an encoding apparatus or decoding apparatus capable of performing the encoding or decoding method.