Synopses & Reviews
Using information and scale as central themes, this comprehensive survey explains how to handle real problems in astronomical data analysis through a modern arsenal of powerful techniques. It treats those innovative methods of image, signal, and data processing that are proving to be both effective and widely relevant. The authors are leaders in this rapidly developing field, and their many decades of experience include leading roles in current international projects such as the Virtual Observatory and the Grid. The book addresses not only students and professional astronomers and astrophysicists, but also serious amateur astronomers and specialists in earth observation, medical imaging, and data mining. The coverage includes chapters or appendices on: detection and filtering; image compression; multichannel, multiscale, and catalog data analytical methods; wavelets transforms, Picard iteration, and software tools.
Synopsis
The use of multiscale analysis methods continues to grow rapidly. Undoubtedly, these methods are of great value when compared to traditional analysis methods. The work presented here is motivated by a vast range of applications in image, signal, and data processing in modern astronomy. The methods explained are innovative, proven in practice, and of wide relevance. This survey of the basic tools and methods also treats recent advances, such as wavelet analysis.
Synopsis
Includes bibliographical references (p. [265]-283) and index.
Table of Contents
Introduction to Applications and Methods -- Filtering -- Deconvolution -- Detection -- Image Compression -- Multichannel Data -- An Entropic Tour of Astronomical Data Analysis -- Astronomical Catalog Analysis -- Multiple Resolution in Data Storage and Retrieval -- Towards the Virtual Observatory -- a Trous Wavelet Transform -- Picard Iteration -- Wavelet Transform Using the Fourier Transform -- Derivative Needed for the Minimization -- Generalization of the Derivative Needed for the Minimization -- Software and Related Developments.