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  • Book
  • © 2002

Astronomical Image and Data Analysis

  • 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

Part of the book series: Astronomy and Astrophysics Library (AAL)

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Table of contents (10 chapters)

  1. Front Matter

    Pages I-XI
  2. Introduction to Applications and Methods

    • Jean-Luc Starck, Fionn Murtagh
    Pages 1-25
  3. Filtering

    • Jean-Luc Starck, Fionn Murtagh
    Pages 27-58
  4. Deconvolution

    • Jean-Luc Starck, Fionn Murtagh
    Pages 59-91
  5. Detection

    • Jean-Luc Starck, Fionn Murtagh
    Pages 93-113
  6. Image Compression

    • Jean-Luc Starck, Fionn Murtagh
    Pages 115-149
  7. Multichannel Data

    • Jean-Luc Starck, Fionn Murtagh
    Pages 151-161
  8. An Entropic Tour of Astronomical Data Analysis

    • Jean-Luc Starck, Fionn Murtagh
    Pages 163-196
  9. Astronomical Catalog Analysis

    • Jean-Luc Starck, Fionn Murtagh
    Pages 197-222
  10. Multiple Resolution in Data Storage and Retrieval

    • Jean-Luc Starck, Fionn Murtagh
    Pages 223-239
  11. Towards the Virtual Observatory

    • Jean-Luc Starck, Fionn Murtagh
    Pages 241-243
  12. Back Matter

    Pages 245-291

About this book

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.

Reviews

"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)

Authors and Affiliations

  • Service d’Astrophysique, Centre d’Etudes de Saclay, Gif-sur-Yvette Cedex, France

    Jean-Luc Starck

  • School of Computer Science, Queen’s University Belfast, Belfast, Northern Ireland, UK

    Fionn Murtagh

Bibliographic Information

Buy it now

Buying options

eBook USD 74.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Other ways to access