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Spline-Based Dense Medial Descriptors for Lossy Image Compression.
Jieying Wang1, Jiří Kosinka1, Alexandru Telea2
1Faculty of Science and Engineering, University of Groningen, 9747 AG Groningen, The Netherlands.
Journal of Imaging
|August 30, 2021
Summary
This study introduces Spline-based Dense Medial Descriptors (SDMD) for image compression. The new method uses B-splines to represent medial descriptors, achieving higher compression ratios than JPEG with comparable image quality.
Area of Science:
- Computer Vision
- Image Processing
- Geometric Modeling
Background:
- Medial descriptors are crucial for image analysis tasks like simplification and compression.
- B-splines are established tools for smooth curve representation in computer graphics.
Purpose of the Study:
- To integrate medial descriptors with B-splines for enhanced image compression.
- To develop an effective vector representation for raster images using B-spline medial descriptors.
Main Methods:
- Modeling medial descriptors using stable and accurate B-splines.
- Implementing the Spline-based Dense Medial Descriptors (SDMD) method.
- Evaluating compression performance against established techniques like JPEG.
Main Results:
- The SDMD method achieves significantly higher compression ratios compared to JPEG.
- Image quality is maintained or improved with the SDMD method.
- B-spline representation offers an effective vector format for raster images.
Conclusions:
- Integrating B-splines with medial descriptors offers a powerful approach for image compression.
- The SDMD method demonstrates superior performance and potential for applications like super-resolution and salient feature preservation.
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