Articles liés à Restoration of Noisy Blurred Images Using FFT and DWT

Restoration of Noisy Blurred Images Using FFT and DWT - Couverture souple

Tahir, Dunia S.; Abdul-Jabbar, Jassim M.

 
9783659783333: Restoration of Noisy Blurred Images Using FFT and DWT
Couverture souple
ISBN 10 : 3659783331 ISBN 13 : 9783659783333
Editeur : LAP LAMBERT Academic Publishing, 2015

Synopsis

Classical methods which can be used to reduce the blurring, noise or both at the same time, such as filtering and iterative methods are discussed. In this era, the need for the faster algorithm is importunate. While all classical iterative methods need iteration numbers between 50 to 100 or more wherever blur and noise increase in the images. In the proposed algorithms, a discrete wavelet transform is used to divide the image into two parts. This partition will help in increasing the manipulation speed of images that are of big sizes. The first part represents the approximation coefficients, the blur is reduced by using the modified fixed-phase iterative algorithm recovery of blurred images. The second part represents the detail coefficients, the noise is removed by using the wavelet thresholding techniques. Many of such techniques are used like; VisuShrink, SureShrink and BayesShrink, in soft and hard thresholding. BayesShrink represents the best method because it can be used for different types of noise with excellent restored images.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

Classical methods which can be used to reduce the blurring, noise or both at the same time, such as filtering and iterative methods are discussed. In this era, the need for the faster algorithm is importunate. While all classical iterative methods need iteration numbers between 50 to 100 or more wherever blur and noise increase in the images. In the proposed algorithms, a discrete wavelet transform is used to divide the image into two parts. This partition will help in increasing the manipulation speed of images that are of big sizes. The first part represents the approximation coefficients, the blur is reduced by using the modified fixed-phase iterative algorithm recovery of blurred images. The second part represents the detail coefficients, the noise is removed by using the wavelet thresholding techniques. Many of such techniques are used like; VisuShrink, SureShrink and BayesShrink, in soft and hard thresholding. BayesShrink represents the best method because it can be used for different types of noise with excellent restored images.

Biographie de l'auteur

Dunia S.Tahir is currently an Assistant Lecturer in Computer Engineering, at the University of Basra. She has received the M.Sc. in Computer Engineering in 2006. She is Ph.D. student now. Her research interests are in the area of digital signal and image processing.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2015
Langue
anglais
ISBN 10 
3659783331
ISBN 13 
9783659783333
Reliure
Broché
Nombre de pages
164
Coordonnées du fabricant
non disponible
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