DocumentCode :
63548
Title :
Non-subsampled contourlet transform based image Denoising in ultrasound thyroid images using adaptive binary morphological operations
Author :
Jai Jaganath Babu, Jayachandiran ; Sudha, Gnanou Florence
Author_Institution :
Dept. of Electron. & Commun. Eng, Pondicherry Eng. Coll., Pondicherry, India
Volume :
8
Issue :
6
fYear :
2014
fDate :
12 2014
Firstpage :
718
Lastpage :
728
Abstract :
Speckle noise reduction is an important preprocessing stage for ultrasound medical image processing. In this paper, a despeckling algorithm is proposed based on non-subsampled contourlet transform. This transform has the property of high directionality, anisotropy and translation invariance, which can be controlled by non-subsampled filter banks. This study aims to denoise the speckle noise in ultrasound images using adaptive binary morphological operations, in order to preserve edges, contours and textures. In morphological operations, structural element plays an important role for image enhancement. In this work, different shapes of structural element have been analysed and filtering parameters have been changed adaptively depending on the nature of the image and the amount of noise in the image. Experimental results of proposed method for natural images, Field II simulated images and real ultrasound images, show that the proposed method is able to preserve edges and image structural details compared with existing methods.
Keywords :
biomedical ultrasonics; channel bank filters; image denoising; image enhancement; image texture; medical image processing; ultrasonic imaging; adaptive binary morphological operations; contour preservation; despeckling algorithm; edge preservation; field II simulated images; filtering parameters; image denoising; image enhancement; image structural details; natural images; nonsubsampled contourlet transform; nonsubsampled filter banks; real ultrasound images; speckle noise denoising; speckle noise reduction; structural element; texture preservation; translation invariance; ultrasound medical image processing; ultrasound thyroid images;
fLanguage :
English
Journal_Title :
Computer Vision, IET
Publisher :
iet
ISSN :
1751-9632
Type :
jour
DOI :
10.1049/iet-cvi.2014.0008
Filename :
6969318
Link To Document :
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