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Fuzzy wavelet and contourlet based contrast enhancement
Ehsan Nezhadarya1, Mohammad B Shamsollahi, Omid Sayadi
1Faculty of Electrical Engineering, Sahand University of Technology, Tabriz, Iran. e_arya@ee.sharif.edu
Summary
This study introduces a novel fuzzy approach for image contrast enhancement using wavelet and contourlet transforms. The method effectively improves image details by enhancing coefficients in both transform domains.
Area of Science:
- Image Processing
- Computer Vision
- Digital Signal Processing
Background:
- Conventional 2D wavelet transforms struggle with representing line-shaped image features due to separability and non-directionality.
- Contourlet transform offers a better alternative for sparse representation of directional features like curves and lines.
Purpose of the Study:
- To develop and evaluate a fuzzy-based approach for image contrast enhancement.
- To leverage the strengths of both wavelet and contourlet transforms for improved image representation and enhancement.
- To create a flexible and understandable enhancement procedure incorporating expert knowledge.
Main Methods:
- A fuzzy approach is proposed for coefficient enhancement in both wavelet and contourlet transform domains.
- Simple fuzzy rules are utilized to modify coefficients, enhancing image contrast.
- The method is applied to separable (wavelet) and nonseparable (contourlet) transforms.
Main Results:
- The proposed fuzzy approach demonstrates effectiveness in enhancing image contrast.
- The method performs well in both wavelet and contourlet transform spaces.
- Implementation results validate the efficacy of the fuzzy enhancement technique.
Conclusions:
- The fuzzy approach offers an effective and flexible method for image contrast enhancement.
- Utilizing fuzzy rules in wavelet and contourlet spaces significantly improves image quality.
- This technique allows for the integration of expert knowledge into the enhancement process.
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