Customer Reviews

Deconvolution of Images and Spectra, Second Edition

5 star:		(0)
4 star:		(2)
3 star:		(0)
2 star:		(0)
1 star:		(0)

 

 

This book is an excellent presentation of exactly what the title says. It starts with a solid mathematical introduction to the topic and then continues with numerous extensions and applications. Recommended if the title interests you.

This book will not serve as a tutorial for those unfamiliar with the mathematics, but it is of great use to people requiring a broad
introduction to deconvolution and also to those interested in other standard and exotic deconvolution methods.

This book covers a wide mathematical path. The reader should have a background in Fourier analysis, convolution theory, and image processing since these topics are mentioned for the purpose of definitions used later in the book. The value of this book is that it brings together from the fields of image processing and spectroscopy many advanced deconvolution methods and how they may be used to remove the characteristic blur inherent in any scientific instrument.

Chapter 1 covers the basic mathematics of Fourier transforms, convolution, and deconvolution. the author then covers spectrometer distortion in Chapter 2. Chapter 3 discusses the linear deconvolution methods such as that of Van Cittert. Nonlinear constrained iterative methods of deconvolution are covered in Chapter 4. Chapter 5 is a short excursion into the convergence of relation algorithms. People unfamiliar with advanced topics, such as projection onto convex sets, Fourier spectrum continuation, and maximum probable estimates of spectra, will gain some understanding from these chapters, but the references listed at the end of the chapters will be required reading.

Since the text covers many deconvolution methods, comparisons between techniques such as Van Cittert's method and Gold's ratio are also included. Readers will have to cover many examples and mathematical algorithms to determine if a deconvolution method is appropriate for their
digital data. Several chapters have an excellent discussion of image deconvolution along with example images before and after deconvolution. The references at the end of each chapter will save the professional many hours of literature searching.

The only reason to reduce the rating down to 4 stars is that this book is currenly out of date.