A novel brain image enhancement method based on nonsubsampled contourlet transform |
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Authors: | Liangliang Li Yujuan Si Zhenhong Jia |
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Affiliation: | 1. College of Communication Engineering, Jilin University, Changchun, China;2. Department of Electronic Information, Zhuhai College of Jilin University, Zhuhai, China;3. College of Information Science and Engineering, Xinjiang University, Urumqi, China |
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Abstract: | In this article, a novel brain image enhancement approach based on nonsubsampled contourlet transform (NSCT) is proposed. First, the image is decomposed into a low‐frequency component and several high‐frequency components by the NSCT; Second, the gamma correction is applied to deal with the low‐frequency sub‐band coefficients, and the adaptive threshold is used to remove the noise of the high‐frequency sub‐bands coefficients; Third, the inverse nonsubsampled contourlet transform is adopted to reconstruct the processed coefficients; Finally, the unsharp filter is used to enhance the reconstructed image. The experimental results demonstrate that the performance of the proposed method is superior to the state‐of‐the‐art algorithms in terms of brain image enhancement. |
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Keywords: | adaptive threshold gamma correction NSCT unsharp filter |
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