Cover Image

Additive and multiplicative noise removal based on adaptive wavelet transformation using cycle spinning

The need for image restoration is encountered in many practical applications. For instance, distortion due to Additive White Gaussian Noise (AWGN) or in some cases the multiplicative (speckle) one can be caused by poor quality image acquisition. Wavelet denoising attempts to remove these types of no...

Full description

Saved in:
Bibliographic Details
Main Authors: Khmag, Asem, Ramli, Abdul Rahman, Syed Mohamed, Syed Abdul Rahman Al-Haddad, Hashim, Shaiful Jahari
Format: Article
Language:English
Published: Science Publications 2014
Online Access:http://psasir.upm.edu.my/id/eprint/36307/1/ajassp.2014.316.328.pdf
http://psasir.upm.edu.my/id/eprint/36307/
http://thescipub.com/abstract/10.3844/ajassp.2014.316.328
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.upm.eprints.36307
record_format eprints
spelling my.upm.eprints.363072017-11-28T08:03:11Z http://psasir.upm.edu.my/id/eprint/36307/ Additive and multiplicative noise removal based on adaptive wavelet transformation using cycle spinning Khmag, Asem Ramli, Abdul Rahman Syed Mohamed, Syed Abdul Rahman Al-Haddad Hashim, Shaiful Jahari The need for image restoration is encountered in many practical applications. For instance, distortion due to Additive White Gaussian Noise (AWGN) or in some cases the multiplicative (speckle) one can be caused by poor quality image acquisition. Wavelet denoising attempts to remove these types of noise present in the signal while preserving the signal characteristics, regardless of its frequency content. A newly developed method based on the wavelet transform (semi-soft thresholding) appears promising, though there is little practical guidance on its use. The results that are obtained by the experiments are compared with traditional additive noise methods such as Sureshrink, Block Method 3 Dimensions (BM3D) and Speckle noise reduction methods as Lee filter, linear scaling filter (Lsmv). Furthermore, Cycle Spinning technique is implemented in order to enhance the quality of the denoised estimates. It has been found that the proposed method achieves better enhancement and restoration of the image while preserving high frequency features of the noiseless image. Moreover, the proposed algorithm matches the quality of the best redundant approaches, while maintaining a high computational efficiency and a low CPU/memory consumption. Science Publications 2014 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/36307/1/ajassp.2014.316.328.pdf Khmag, Asem and Ramli, Abdul Rahman and Syed Mohamed, Syed Abdul Rahman Al-Haddad and Hashim, Shaiful Jahari (2014) Additive and multiplicative noise removal based on adaptive wavelet transformation using cycle spinning. American Journal of Applied Sciences, 11 (2). pp. 316-328. ISSN 1546-9239; ESSN: 1554-3641 http://thescipub.com/abstract/10.3844/ajassp.2014.316.328 10.3844/ajassp.2014.316.328
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description The need for image restoration is encountered in many practical applications. For instance, distortion due to Additive White Gaussian Noise (AWGN) or in some cases the multiplicative (speckle) one can be caused by poor quality image acquisition. Wavelet denoising attempts to remove these types of noise present in the signal while preserving the signal characteristics, regardless of its frequency content. A newly developed method based on the wavelet transform (semi-soft thresholding) appears promising, though there is little practical guidance on its use. The results that are obtained by the experiments are compared with traditional additive noise methods such as Sureshrink, Block Method 3 Dimensions (BM3D) and Speckle noise reduction methods as Lee filter, linear scaling filter (Lsmv). Furthermore, Cycle Spinning technique is implemented in order to enhance the quality of the denoised estimates. It has been found that the proposed method achieves better enhancement and restoration of the image while preserving high frequency features of the noiseless image. Moreover, the proposed algorithm matches the quality of the best redundant approaches, while maintaining a high computational efficiency and a low CPU/memory consumption.
format Article
author Khmag, Asem
Ramli, Abdul Rahman
Syed Mohamed, Syed Abdul Rahman Al-Haddad
Hashim, Shaiful Jahari
spellingShingle Khmag, Asem
Ramli, Abdul Rahman
Syed Mohamed, Syed Abdul Rahman Al-Haddad
Hashim, Shaiful Jahari
Additive and multiplicative noise removal based on adaptive wavelet transformation using cycle spinning
author_facet Khmag, Asem
Ramli, Abdul Rahman
Syed Mohamed, Syed Abdul Rahman Al-Haddad
Hashim, Shaiful Jahari
author_sort Khmag, Asem
title Additive and multiplicative noise removal based on adaptive wavelet transformation using cycle spinning
title_short Additive and multiplicative noise removal based on adaptive wavelet transformation using cycle spinning
title_full Additive and multiplicative noise removal based on adaptive wavelet transformation using cycle spinning
title_fullStr Additive and multiplicative noise removal based on adaptive wavelet transformation using cycle spinning
title_full_unstemmed Additive and multiplicative noise removal based on adaptive wavelet transformation using cycle spinning
title_sort additive and multiplicative noise removal based on adaptive wavelet transformation using cycle spinning
publisher Science Publications
publishDate 2014
url http://psasir.upm.edu.my/id/eprint/36307/1/ajassp.2014.316.328.pdf
http://psasir.upm.edu.my/id/eprint/36307/
http://thescipub.com/abstract/10.3844/ajassp.2014.316.328
_version_ 1643831707803058176
score 13.211869

Similar Items