J. -L. Starck, F. Murtagh

Astronomical Image and Data Analysis (eBook, PDF)

• Format: PDF

Produktbeschreibung

Thisbookpresentsmaterialwhichismorealgorithmicallyorientedthanmost alternatives.Italsodealswithtopicsthatareatorbeyondthestateoftheart. Examples include practical and applicable wavelet and other multiresolution transform analysis. New areas are broached like the ridgelet and curvelet transforms. The reader will ?nd in this book an engineering approach to the interpretation of scienti?c data. Compared to the 1st Edition, various additions have been made throu- out, and the topics covered have been updated. The background or en- ronment of this book's topics include continuing interest in e-science and the virtual observatory, which are based on web based and increasingly web service based science and engineering. Additional colleagues whom we would like to acknowledge in this 2nd edition include: Bedros Afeyan, Nabila Aghanim, Emmanuel Cand` es, David Donoho, Jalal Fadili, and Sandrine Pires, We would like to particularly - knowledge Olivier Forni who contributed to the discussion on compression of hyperspectral data, Yassir Moudden on multiwavelength data analysis and Vicent Mart¿ ?nez on the genus function. The cover image to this 2nd edition is from the Deep Impact project. It was taken approximately 8 minutes after impact on 4 July 2005 with the CLEAR6 ?lter and deconvolved using the Richardson-Lucy method. We thank Don Lindler, Ivo Busko, Mike A'Hearn and the Deep Impact team for the processing of this image and for providing it to us.

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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 338
• Erscheinungstermin: 21. Juni 2007
• Englisch
• ISBN-13: 9783540330257
• Artikelnr.: 37370859

Inhaltsangabe

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.- Appendix A: A trous Wavelet Transform.- Appendix B: Picard Iteration.- Appendix C: Wavelet Transform Using the Fourier Transform.- Appendix D: Derivative Needed for the Minimization.- Appendix E: Generalization of the Derivative Needed for Minimization.- Appendix F: Software and Related Developments.-References.- Index.

Rezensionen

"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)