Deblurring Images
Matrices, Spectra, and Filtering

This book provides a unique insight to the mathematics of image deblurring.

Per Christian Hansen (Author), James G. Nagy (Author), Dianne P. O'Leary (Author)

9780898716184, Society for Industrial and Applied Mathematics

Paperback / softback, published 29 March 2007

144 pages
25.2 x 17.4 x 0.7 cm, 0.31 kg

'The book's focus on imaging problems is very unique among the competing books on inverse and ill-posed problems … It gives a nice introduction into the MATLAB world of images and deblurring problems.' Martin Hanke, Johannes-Gutenberg-Universität

In image deblurring, the goal is to recover the original, sharp image by using a mathematical model of the blurring process. The key issue is that some information on the lost details is indeed present in the blurred image, but this 'hidden' information can be recovered only if we know the details of the blurring process. Deblurring Images: Matrices, Spectra, and Filtering 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 MATLAB® implementations described in the book provide a template of techniques that can be used to restore blurred images from many applications.

Preface
How to Get the Software
List of Symbols
1. The Image Deblurring Problem
2. Manipulating Images in MATLAB
3. The Blurring Function
4. Structured Matrix Computations
5. SVD and Spectral Analysis
6. Regularization by Spectral Filtering
7. Color Images, Smoothing Norms, and Other Topics
Appendix: MATLAB Functions
Bibliography
Index.

Subject Areas: Computer vision [UYQV], Photo & image editing [UGP], Mathematical modelling [PBWH], Applied mathematics [PBW]