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A Medical Image Denoising Method using Subband Adaptive Thresholding Based on a Shearlet Transform
Serdica Journal of Computing, Tome 10 (2016) no. 3-4, pp. 219-230 Cet article a éte moissonné depuis la source Bulgarian Digital Mathematics Library

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The image denoising process is of great importance when analyzing images and their visualization. A major problem is finding the boundary between clearing the noise and keeping the salient features in the images. This paper proposes adaptive subband threshold image denoising in a shearlet domain based on the Shannon entropy. The method does not suppose a specific type of noise, it does not require data for its spectrum, nor does it lead to highly complex computational algorithms. ACM Computing Classification System (1998): I.5.4, I.4.3, I.4.5.
Keywords: Medical Image, Denoising, Shearlet Tresholding, Shannon Entropy, Rician Noise 
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     author = {Petrov, Miroslav},
     title = {A {Medical} {Image} {Denoising} {Method} using {Subband} {Adaptive} {Thresholding} {Based} on a {Shearlet} {Transform}},
     journal = {Serdica Journal of Computing},
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     year = {2016},
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     number = {3-4},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/SJC_2016_10_3-4_a1/}
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Petrov, Miroslav. A Medical Image Denoising Method using Subband Adaptive Thresholding Based on a Shearlet Transform. Serdica Journal of Computing, Tome 10 (2016) no. 3-4, pp. 219-230. http://geodesic.mathdoc.fr/item/SJC_2016_10_3-4_a1/