Synopses & Reviews
Deconvolution of Images and Spectra is a Second Edition of Janssons 1984 book,
Deconvolution: With Applications in Spectroscopy. This landmark volume was the first published on deconvolution to provide both an overview of the field, and practical methods and results. In the twelve years since the first book was published, major advances have taken place. For example, researchers have refined projections onto convex sets, improved understanding of other relaxation methods, applied principles of neural networks, and extended the most effective nonlinear methods to image processing.
The significant advances in the years since the First Edition have created the need for this Second Edition, which addresses both the most recent and effective nonlinear constrained methods, and their practical application to a variety scientific and engineering fields. Deconvolution of Images and Spectra embraces all the advantages of its predecessor by conveying a clear understanding while providing a selection of effective and practical techniques. The authors assume only a working knowledge ofcalculus, and emphasize practical applications over topics of purely theoretical interest, focusing on areas that have been pivotal to the evolution of the most effective methods. This tutorial is essentially self-contained; readers will find it to be easy to understand and practical.
Key Features
* Reviews concepts important in the development of the deconvolution field
* Includes four completely new chapters presenting material on projections onto convex sets, convergence of relaxation methods, and adaptations to image processing in microscopy and astronomy
* Emphasizes the most effective constrained methods
* Introduces deconvolution to the beginner
* Includes recent advances
* Unifies and connects varied approaches
* Applies to diverse fields
* Details applications to image processing and spectroscopy, especially infrared and electron spectroscopy
* Provides a guide to the literature
Review
"This is an excellent practical handbook for using deconvolution with real data for which the positivity contstraint is useful, such as in optical images and spectra...Figures are clear and the text is very readable...We are happy to have this book and recommend it to anyone involved in data analysis or signal processing which involves deconvolution."
--AMERICAN SCIENTIST
Synopsis
Deconvolution is a technique in signal or image processing that is applied when data is difficult to read due to spreading and blurring of corrupt images and experimental results. Deconvolution of Images and Spectra is a second edition of Jansson's 1984 book, Deconvolution with Applications in Spectroscopy (Academic Press). This landmark volume was first published to provide both an overview of the field, and practical methods and results. In the twelve years since the first book was published, major advances have been made in the field.
Deconvolution of Images and Spectra includes all the advantages of its predecessor by conveying a clear understanding of the field while providing a selection of effective, practical techniques. The authors assume only a working knowledge of calculus, and emphasize practical applications over topics of theoretical interest, focusing on areas that have been pivotal to the evolution of the most effective methods. This tutorial is essentially self-contained, and readers will find it practical and easy to understand.
Synopsis
Deconvolution of Images and Spectra is a Second Edition of Janssons 1984 book, Deconvolution: With Applications in Spectroscopy. This landmark volume was the first published on deconvolution to provide both an overview of the field, and practical methods and results. In the twelve years since the first book was published, major advances have taken place. For example, researchers have refined projections onto convex sets, improved understanding of other relaxation methods, applied principles of neural networks, and extended the most effective nonlinear methods to image processing.
The significant advances in the years since the First Edition have created the need for this Second Edition, which addresses both the most recent and effective nonlinear constrained methods, and their practical application to a variety scientific and engineering fields. Deconvolution of Images and Spectra embraces all the advantages of its predecessor by conveying a clear understanding while providing a selection of effective and practical techniques. The authors assume only a working knowledge ofcalculus, and emphasize practical applications over topics of purely theoretical interest, focusing on areas that have been pivotal to the evolution of the most effective methods. This tutorial is essentially self-contained; readers will find it to be easy to understand and practical.
Key Features
x Reviews concepts important in the development of the deconvolution field
x Includes four completely new chapters presenting material on projections onto convex sets, convergence of relaxation methods, and adaptations to image processing in microscopy and astronomy
x Emphasizes the most effective constrained methods
x Introduces deconvolution to the beginner
x Includes recent advances
x Unifies and connects varied approaches
x Applies to diverse fields
x Details applications to image processing and spectroscopy, especially infrared and electron spectroscopy
x Provides a guide to the literature
Synopsis
ill find it practical and easy to understand.
Table of Contents
P.A. Jansson, Convolution and Related Concepts.
P.A. Jansson, Distortion of Optical Spectra.
P.A. Jansson, Traditional Linear Deconvolution Methods.
P.A. Jansson, Modern Constrained Nonlinear Methods.
P.C. Crilly, Convergence of Relaxation Algorithms.
W.E. Blass and G.W. Halsey, Instrumental Considerations.
P.C. Crilly, W.E. Blass, and G.W. Halsey, Deconvolution Examples.
R.D. Davies and P.A. Jansson, Application to Electron Spectroscopy for Chemical Analysis.
J.R. Swedlow, J.W. Sedat, and D.A. Agard, Deconvolution in Optical Microscopy.
R.J. Hanisch, R.L. White, and R.L. Gilliland, Deconvolution of Hubble Space Telescope Images and Spectra.
B. Roy Frieden, Maximum Liklihood Estimates of Spectra.
S.J. Howard, Fourier Spectrum Continuation.
S.J. Howard, Minimum Negativity Fourier Spectrum Continuation.
R.J. Marks, II, Alternating Projection onto Convex Sets.