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