Please use this identifier to cite or link to this item: http://gukir.inflibnet.ac.in:8080/jspui/handle/123456789/4512
Title: Speckle reducing contourlet transform for medical ultrasound images
Authors: Hiremath P.S
Akkasaligar P.T
Badiger S.
Keywords: Contourlet transform
Despeckling
Pyramidal directional filter bank
Thresholding
Issue Date: 2011
Citation: World Academy of Science, Engineering and Technology , Vol. 80 , , p. 1217 - 1224
Abstract: Speckle noise affects all coherent imaging systems including medical ultrasound. In medical images, noise suppression is a particularly delicate and difficult task. A tradeoff between noise reduction and the preservation of actual image features has to be made in a way that enhances the diagnostically relevant image content. Even though wavelets have been extensively used for denoising speckle images, we have found that denoising using contourlets gives much better performance in terms of SNR, PSNR, MSE, variance and correlation coefficient. The objective of the paper is to determine the number of levels of Laplacian pyramidal decomposition, the number of directional decompositions to perform on each pyramidal level and thresholding schemes which yields optimal despeckling of medical ultrasound images, in particular. The proposed method consists of the log transformed original ultrasound image being subjected to contourlet transform, to obtain contourlet coefficients. The transformed image is denoised by applying thresholding techniques on individual band pass sub bands using a Bayes shrinkage rule. We quantify the achieved performance improvement.
URI: http://gukir.inflibnet.ac.in:8080/jspui/handle/123456789/4512
Appears in Collections:1. Journal Articles

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