num_pages: 144
description: 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 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.
language: English
title: Deblurring Images: Matrices, Spectra, and Filtering
titlecomplete: Deblurring Images: Matrices, Spectra, and Filtering (Fundamentals of Algorithms, Series Number 3)
ratings_count: 3
publisher: Society for Industrial and Applied Mathematics