Blind image deconvolution : theory and applications

Bibliographic Information

Blind image deconvolution : theory and applications

edited by Patrizio Campisi, Karen Egiazarian

CRC Press, c2007

Available at  / 10 libraries

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Includes bibliographical references and index

Description and Table of Contents

Description

Blind image deconvolution is constantly receiving increasing attention from the academic as well the industrial world due to both its theoretical and practical implications. The field of blind image deconvolution has several applications in different areas such as image restoration, microscopy, medical imaging, biological imaging, remote sensing, astronomy, nondestructive testing, geophysical prospecting, and many others. Blind Image Deconvolution: Theory and Applications surveys the current state of research and practice as presented by the most recognized experts in the field, thus filling a gap in the available literature on blind image deconvolution. Explore the gamut of blind image deconvolution approaches and algorithms that currently exist and follow the current research trends into the future. This comprehensive treatise discusses Bayesian techniques, single- and multi-channel methods, adaptive and multi-frame techniques, and a host of applications to multimedia processing, astronomy, remote sensing imagery, and medical and biological imaging at the whole-body, small-part, and cellular levels. Everything you need to step into this dynamic field is at your fingertips in this unique, self-contained masterwork. For image enhancement and restoration without a priori information, turn to Blind Image Deconvolution: Theory and Applications for the knowledge and techniques you need to tackle real-world problems.

Table of Contents

Blind image Deconvolution: Problem Formulation and Existing Approaches. Blind Image Deconvolution using Bussgang Techniques. Applications to Image Deblurring and Texture Synthesis. Blind Multiframe Image Deconvolution Using Anisotropic Spatially Adaptive Filtering for Denoising and Regularization. Bayesian Methods Based on Variational Approximations for Blind Image Deconvolution. Deconvolution of Medical Images from Microscopic to Whole Body Images. Bayesian Estimation of Blur and Noise in Remote Sensing Imaging. Deconvolution and Blind Deconvolution in Astronomy. Multiframe Blind Deconvolution Coupled with Frame Registration and Resolution Enhancement. Blind Reconstruction of Multiframe Imagery Based on Fusion and Classification. Blind Deconvolution and Structured Matrix Computations with Applications to Array Imaging. Index.

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