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Projection-based spatially adaptive reconstruction of block-transform compressed images
Y Yang1, N P Galatsanos, A K Katsaggelos
1Dept. of Electr. and Comput. Eng., Illinois Inst. of Technol., Chicago, IL.
Summary
This study introduces a new image recovery method for block-transform coding, improving decoded image quality by enforcing between-block smoothness. The novel algorithm outperforms existing deblocking techniques.
Area of Science:
- Computer Vision
- Image Processing
- Signal Processing
Background:
- Block-transform coding is a prevalent image compression technique.
- Current decoding methods rely solely on transmitted transform data, often leading to artifacts.
Purpose of the Study:
- To enhance image decoding by treating it as an image recovery problem.
- To develop a novel algorithm that leverages prior knowledge of image continuity.
Main Methods:
- Formulating image decoding as an image recovery problem.
- Proposing a spatially adaptive algorithm based on projections onto convex sets.
- Introducing a new constraint set for between-block smoothness, incorporating local statistics and perceptual characteristics.
Main Results:
- The proposed algorithm effectively enforces between-block smoothness.
- A simplified version with complexity analysis was also developed.
- Numerical experiments demonstrated superior performance compared to JPEG deblocking and prior projection-based methods.
Conclusions:
- The novel image recovery approach significantly improves decoded image quality.
- Incorporating between-block smoothness constraints enhances deblocking performance.
- The algorithm offers a promising advancement in image compression and recovery.
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