Call Boomerang Books 1300 36 33 32

Get Latest Book News + FREE Shipping. Subscribe to the Boomerang Books Bulletin eNewsletter right now!

Description - Deblurring Images by Per Christian Hansen

When we use a camera, we want the recorded image to be a faithful representation of the scene that we see, but every image is more or less blurry. 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 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(R) implementations described in the book provide a template of techniques that can be used to restore blurred images from many applications. This book's treatment of image deblurring is unique in two ways: it includes algorithmic and implementation details; and by keeping the formulations in terms of matrices, vectors, and matrix computations, it makes the material accessible to a wide range of readers. Students and researchers in engineering will gain an understanding of the linear algebra behind filtering methods, while readers in applied mathematics, numerical analysis, and computational science will be exposed to modern techniques to solve realistic large-scale problems in image processing. With a focus on practical and efficient algorithms, Deblurring Images includes many examples, sample image data, and MATLAB codes that allow readers to experiment with the algorithms. It also incorporates introductory material, such as how to manipulate images within the MATLAB environment, making it a stand-alone text. Pointers to the literature are given for techniques not covered in the book.

Buy Deblurring Images by Per Christian Hansen from Australia's Online Independent Bookstore, Boomerang Books.

Book Details

ISBN: 9780898716184
ISBN-10: 0898716187
Format: Paperback
(229mm x 152mm x 7mm)
Pages: 144
Imprint: Society for Industrial & Applied Mathematics,U.S.
Publisher: Society for Industrial & Applied Mathematics,U.S.
Publish Date: 30-Oct-2006
Country of Publication: United States

Book Reviews - Deblurring Images by Per Christian Hansen

» Have you read this book? We'd like to know what you think about it - write a review about Deblurring Images book by Per Christian Hansen and you'll earn 50c in Boomerang Bucks loyalty dollars (you must be a Boomerang Books Account Holder - it's free to sign up and there are great benefits!)

Write Review

Author Biography - Per Christian Hansen

Per Christian Hansen is Professor of Scientific Computing at the Technical University of Denmark. He has also worked at the University of Copenhagen, Denmark, and the Danish Computing Center for Research and Education (UNI*C). His publications include a research monograph, several MATLAB packages, and many papers on inverse problems, matrix computations, and signal processing. He is a member of SIAM. James G. Nagy is Professor of Mathematics and Computer Science at Emory University. In 2001 he was selected to hold the Emory Professorship for Distinguished Teaching in the Social and Natural Sciences. He has published many research papers on scientific computing, numerical linear algebra, inverse problems, and image processing. He is a member of SIAM and AWM. Dianne P. O'Leary is Professor of Computer Science at the University of Maryland and a mathematician at the U.S. National Institute of Standards and Technology. She was awarded an honorary Doctorate of Mathematics from the University of Waterloo. She is the author of over 75 publications on numerical analysis and computational science and over 25 publications on education and mentoring. She is a member of SIAM, AWM, and ACM.