Astronomical Image and Data Analysis
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Beschreibung
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.
When we consider the ever increasing amount of astronomical data available to us, we can well say that the needs of modern astronomy are growing by the day. Ever better observing facilities are in operation. The fusion of infor mation leading to the coordination of observations is of central importance. The methods described in this book can provide effective and efficient ripostes to many of these issues. Much progress has been made in recent years on the methodology front, in line with the rapid pace of evolution of our technological infrastructures. The central themes of this book are information and scale. The approach is astronomy-driven, starting with real problems and issues to be addressed. We then proceed to comprehensive theory, and implementations of demonstrated efficacy. The field is developing rapidly. There is little doubt that further important papers, and books, will follow in the future. Colleagues we would like to acknowledge include: Alexandre Aussem, Albert Bijaoui, Franc;ois Bonnarel, Jonathan G. Campbell, Ghada Jammal, Rene Gastaud, Pierre-Franc;ois Honore, Bruno Lopez, Mireille Louys, Clive Page, Eric Pantin, Philippe Querre, Victor Racine, Jerome Rodriguez, and Ivan Valtchanov.
Algorithmically oriented handbook on basic tools in Astronomical Data Analysis aimed at observing astronomers Unique especially in its treatment of wavelet analysis and can also be used for classroom work There are practically no books available on this important topic Includes supplementary material: sn.pub/extras
Autor*in
J.-L. Starck
Themen in »Astronomical Image and Data Analysis«
Astronomical Cataloge Astronomical Data Analysis Data Filtering Data Storage Image Compression Multiscale Analysis Observational Astronomy Pattern Recognition Virtual Observatory Wavelet Analyis astronomy
Stimmen zu »Astronomical Image and Data Analysis«
"This book is an authoritative and thorough account of numerous mathematical techniques used by research astronomers and I can strongly recommend it for those purposes." (C.R. Kitchin, Astronomy Now, Oct. 2003)
"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." (Europe & Astronomy, 905, 2003)
"The phenomenal amounts of data produced by modern telescopes require powerful tools to extract whatever valuable nuggets of information they contain from the dross of unwanted signal and noise. Computer power available to reduce the data is barely sufficient to keep pace. This monograph is aimed at solving these problems by a variety of different methods. [...] The book includes a number of well-chosen illustrative examples, some based on real, and others on artificial data. It also has a substantial bibliography. However it is not a guide to the several excellent reduction packages currently available. Rather it is a thorough investigation of how astronomical images can be modelled and how the maximum information can be extracted from the noise, and for this it can be recommended." (The Observatory, 123/1174, 2003)
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