An Improved Image Denoising Algorithm Based on Structural Similarity and Curvelet |
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Authors: | HE Ruo-nan YANG Wei-wei LI Mei |
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Institution: | Institute of Electronic and Information, Jiangsu University of Science and Technology,Zhenjiang Jiangsu,212003,China |
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Abstract: | An image denoising method based on curvelet within the framework of non-local means(NLM) is proposed in this paper. We use Structural Similarity(SSIM) to compute the value of SSIM between the reference patch and its similar versions, and remove the dissimilar pixels. Besides, the curvelet is adopted to adjust the coefficients of these patches with low SSIM. Experiments show that the proposed method has the capacity to denoise effectively, improves the peak signal-to-noise ratio of the image, and keeps better visual result in edges information reservation as well. |
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Keywords: | Non local-mean (NLM) Image denoising Curvelet Structural similarity |
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