Medical image enhancement algorithm based on NSCT and the improved fuzzy contrast |
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| Authors: | Jing-jing Wang Zhen‐hong Jia Xi‐zhong Qin Jie Yang Nikola Kasabov |
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| Affiliation: | 1. College of Information Science and Engineering, Xinjiang University, Urumqi, China;2. Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University, Shanghai, China;3. Knowledge Engineering and Discovery Research Institute, Auckland University of Technology Auckland 1020, New Zealand |
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| Abstract: | In order to solve the problem of noise amplification, low contrast and image distortion in the process of medical image enhancement, a new algorithm is proposed which combines NSCT (nonsubsampled contourlet transform) and improved fuzzy contrast. The image is decomposed by NSCT. Firstly, linear enhancement method is used in low frequency coefficients; secondly the improved adaptive threshold function is used to deal with the high frequency coefficients. Finally, the improved fuzzy contrast is used to enhance the global contrast and the Laplace operator is used to enhance the details of the medical images. Experimental results show that the proposed algorithm can improve the image visual effects, remove the noise and enhance the details of medical images. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 7–14, 2015 |
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| Keywords: | medical images NSCT transform adaptive threshold function fuzzy contrast |
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