IMI-BAS BAS
 

BulDML at Institute of Mathematics and Informatics >
IMI >
IMI Periodicals >
Serdica Journal of Computing >
2016 >
Volume 10 Number 3-4 >

Please use this identifier to cite or link to this item: http://hdl.handle.net/10525/2925

Title: A Medical Image Denoising Method using Subband Adaptive Thresholding Based on a Shearlet Transform
Authors: Petrov, Miroslav
Keywords: Medical Image
Denoising
Shearlet Tresholding
Shannon Entropy
Rician Noise
Issue Date: 2016
Publisher: Institute of Mathematics and Informatics Bulgarian Academy of Sciences
Citation: Serdica Journal of Computing, Vol. 10, No 3-4, (2016), 219p-230p
Abstract: 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.
URI: http://hdl.handle.net/10525/2925
ISSN: 1312-6555
Appears in Collections:Volume 10 Number 3-4

Files in This Item:

File Description SizeFormat
sjc-vol10-num3-4-2016-p219-p230.pdf642.47 kBAdobe PDFView/Open

 



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0!   Creative Commons License