Isbn: 9783659783333 - restoration of noisy blurred images using fft and dwt (7 risultati)

Taschenbuch. Condizione: Neu. Restoration of Noisy Blurred Images Using FFT and DWT | Dunia S. Tahir (u. a.) | Taschenbuch | 164 S. | Englisch | 2015 | LAP LAMBERT Academic Publishing | EAN 9783659783333 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

Paperback. Condizione: Brand New. 164 pages. 8.66x5.91x0.37 inches. In Stock.

paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 164 pp. Englisch.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.…

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Tahir Dunia S.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 t.…

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 164 pp. Englisch.…