Restoration of Noisy Blurred Images Using FFT and DWT
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Restoration of Noisy Blurred Images Using FFT and DWT
ISBN: 9783659783333 bzw. 3659783331, vermutlich in Englisch, neu, Hörbuch.
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.
Restoration of Noisy Blurred Images Using FFT and DWT
ISBN: 9783659783333 bzw. 3659783331, vermutlich in Englisch, LAP Lambert Academic Publishing, Taschenbuch, neu.
Restoration of Noisy Blurred Images Using FFT and DWT: 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. Englisch, Taschenbuch.
Restoration of Noisy Blurred Images Using FFT and Dwt (2015)
ISBN: 9783659783333 bzw. 3659783331, in Deutsch, Lap Lambert Academic Publishing, Taschenbuch, neu.
bol.com.
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 manipulatio... 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.Taal: Engels;Afmetingen: 10x229x152 mm;Gewicht: 249,00 gram;Verschijningsdatum: september 2015;ISBN10: 3659783331;ISBN13: 9783659783333; Engelstalig | Paperback | 2015.
Restoration of Noisy Blurred Images Using FFT and DWT (2015)
ISBN: 9783659783333 bzw. 3659783331, in Englisch, 164 Seiten, LAP LAMBERT Academic Publishing, Taschenbuch, neu.
جديد من: $69.19 (9 ويقدم)
تستخدم من: $84.31 (2 ويقدم)
إظهار المزيد 11 ويقدم في Amazon.com
Von Händler/Antiquariat, Book Depository US.
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. Paperback, التسمية: LAP LAMBERT Academic Publishing, LAP LAMBERT Academic Publishing, مجموعة المنتجات: Book, ونشرت: 2015-09-25, تاريخ الإصدار: 2015-09-25, ستوديو: LAP LAMBERT Academic Publishing.
Restoration of Noisy Blurred Images Using FFT and DWT (2015)
ISBN: 9783659783333 bzw. 3659783331, in Englisch, 164 Seiten, LAP LAMBERT Academic Publishing, Taschenbuch, gebraucht.
جديد من: $69.19 (9 ويقدم)
تستخدم من: $84.31 (2 ويقدم)
إظهار المزيد 11 ويقدم في Amazon.com
Von Händler/Antiquariat, super_star_seller.
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. Paperback, التسمية: LAP LAMBERT Academic Publishing, LAP LAMBERT Academic Publishing, مجموعة المنتجات: Book, ونشرت: 2015-09-25, تاريخ الإصدار: 2015-09-25, ستوديو: LAP LAMBERT Academic Publishing.
Restoration of Noisy Blurred Images Using FFT and DWT (2016)
ISBN: 9783659783333 bzw. 3659783331, in Deutsch, neu, Nachdruck.
Von Händler/Antiquariat, Ria Christie Collections.
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Restoration of Noisy Blurred Images Using FFT and DWT
ISBN: 3659783331 bzw. 9783659783333, vermutlich in Englisch, LAP Lambert Academic Publishing, Taschenbuch, neu.