Matrices, Spectra, and Filtering
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Deblurring Images by Per Christian Hansen
Book DescriptionIn 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(R) 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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Book DetailsISBN: 9780898716184
(228mm x 152mm x 7mm)
Imprint: Society for Industrial & Applied Mathematics,U.S.
Publisher: Society for Industrial & Applied Mathematics,U.S.
Publish Date: 29-Mar-2007
Country of Publication: United States
Books By Author Per Christian Hansen
Discrete Inverse Problems, Paperback (March 2010)
An introduction to the practical treatment of inverse problems using numerical methods for graduate students, including examples and exercises.
Rank-deficient and Discrete Ill-posed Problems, Paperback (January 1987)» View all books by Per Christian Hansen
An overview of modern computational stabilization methods for linear inversion: applications to audio processing, medical imaging, seismology and other areas.
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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.
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