Deblurring images : matrices, spectra, and filtering / Per Christian Hansen, James G. Nagy, Dianne P. O'Leary.

Describes the deblurring algorithms and techniques collectively known as spectral filtering methods, in which the singular value decomposition, or a similar decomposition with spectral properties, is used to introduce the necessary regularization or filtering in the reconstructed image. The concise...

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Bibliographic Details
Online Access: Full Text (via SIAM)
Main Author: Hansen, Per Christian
Corporate Author: Society for Industrial and Applied Mathematics
Other Authors: Nagy, James G., O'Leary, Dianne P.
Other title:Deblurrinq images.
Deblurring Images: Matrices, Spectra and Filtering.
Format: eBook
Language:English
Published: Philadelphia, Pa. : Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104), 2006.
[Place of publication not identified] : SIAM Society for Industrial and Applied Mathematics, 2006.
Series:Fundamentals of algorithms.
Subjects:

MARC

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245 1 0 |a Deblurring images :  |b matrices, spectra, and filtering /  |c Per Christian Hansen, James G. Nagy, Dianne P. O'Leary. 
246 3 |a Deblurrinq images. 
246 3 |a Deblurring Images: Matrices, Spectra and Filtering. 
260 |a Philadelphia, Pa. :  |b Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104),  |c 2006. 
264 1 |a [Place of publication not identified] :  |b SIAM Society for Industrial and Applied Mathematics,  |c 2006. 
300 |a 1 electronic resource (xiv, 130 pages) :  |b illustrations (some color) 
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490 1 |a Fundamentals of algorithms. 
504 |a Includes bibliographical references (pages 121-125) and index. 
505 0 |a The Image Deblurring Problem -- Manipulating Images in MATLAB -- The Blurring Function -- Structured Matrix Computations -- SVD and Spectral Analysis -- Regularization by Spectral Filtering -- Color Images, Smoothing Norms, and Other Topics -- Appendix : MATLAB Functions. 
520 3 |a Describes the deblurring algorithms and techniques collectively known as spectral filtering methods, in which the singular value decomposition, or a similar decomposition with spectral properties, is used to introduce the necessary regularization or filtering in the reconstructed image. The concise MATLABʼ implementations described in the book provide a template of techniques that can be used to restore blurred images from many applications. 
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