International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 49 - Number 14 |
Year of Publication: 2012 |
Authors: Romain Mavudila Kongo, Mohammed Cherkaoui, Lhousaine Masmoudi, Najem Hassanain |
10.5120/7698-1033 |
Romain Mavudila Kongo, Mohammed Cherkaoui, Lhousaine Masmoudi, Najem Hassanain . A Combined Dual-Tree Complex Wavelet (DT-CWT) and Bivariate Shrinkage for Ultrasound Medical Images Despeckling. International Journal of Computer Applications. 49, 14 ( July 2012), 42-49. DOI=10.5120/7698-1033
In this paper, an efficient DT-CWT based method for medical ultrasound images despeckling is presented. The ultrasound images are often deteriorated by speckle noise, this noise is a random granular texture that obscures anatomy in ultrasound images and degrades the detectability of low-contrast lesions. Speckle noise occurrence is often undesirable, since it affects the tasks of human interpretation and diagnosis. Different from many other schemes with wavelet transform are used on one side in which the studies have dealt more with the standard DWT case. However, the Discrete Wavelet Transform (DWT) has some disadvantages that undermine its application in image processing. In this study we investigated a performances complex wavelet transform (DT-CWT) combined with Bivariate Shrinkage. The proposed method was tested on a noisy ultrasound medical image, and the restored images show a great effectiveness of DT-CWT method compared to the classical DWT.