Curvelet based nonlocal means algorithm for image denoising

In this work, a curvelet based nonlocal means denoising method is proposed. In the proposed method, the curvelet transform is firstly implemented on the noisy image to produce reconstructed images. Then the similarity of two pixels in the noisy image is computed based on these reconstructed images w...

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Bibliographic Details
Published in:International journal of electronics and communications 2014-01, Vol.68 (1), p.37-43
Main Authors: Wu, Kaizhi, Zhang, Xuming, Ding, Mingyue
Format: Article
Language:English
Subjects:
Curvelet transform
Image denoising
Image reconstruction
Nonlocal means
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Summary:In this work, a curvelet based nonlocal means denoising method is proposed. In the proposed method, the curvelet transform is firstly implemented on the noisy image to produce reconstructed images. Then the similarity of two pixels in the noisy image is computed based on these reconstructed images which include complementary image features at relatively high noise levels or both the reconstructed images and the noisy image at relatively low noise levels. Finally, the pixel similarity and the noisy image are utilized to obtain the final denoised result using the nonlocal means method. Quantitative and visual comparisons demonstrate that the proposed method outperforms the state-of-art nonlocal means denoising methods in terms of noise removal and detail preservation.
ISSN:1434-8411
1618-0399
DOI:10.1016/j.aeue.2013.07.011