Image Processing and Data Analysis: The Multiscale Approach

An introduction to a range of techniques for the analysis of digital data, especially the manipulation of images. Contains real-world examples in astronomy, electrical engineering, physics, geophysics and medical imaging.

**Tag(s):**
Signal Processing

**Publication date**: 01 Jul 1998

**ISBN-10**:
0521599148

**ISBN-13**:
978-052159914

**Paperback**:
315 pages

**Views**: 20,511

Image Processing and Data Analysis: The Multiscale Approach

An introduction to a range of techniques for the analysis of digital data, especially the manipulation of images. Contains real-world examples in astronomy, electrical engineering, physics, geophysics and medical imaging.

Book Excerpts:

Number of techniques have been developed in recent years for the analysis of digital data, especially the manipulation of images. This book provides an in-depth introduction to a range of these data-processing techniques. It develops the reader's understanding of each technique and then shows with practical examples how they can be applied to improve the skills of graduate students and researchers in astronomy, electrical engineering, physics, geophysics and medical imaging.

What sets this book apart from others on the subject is the complementary blend of theory and practical application. Throughout, the book is illustrated with real-world examples from astronomy, electrical engineering, remote sensing and medicine. It also shows how many, more traditional, methods can be enhanced by incorporating the wavelet and multiscale methods into the processing.

For graduate students and researchers already experienced in image processing and data analysis, this book provides a guide to a wide range of data-analysis techniques.

Review(s):

Amazon.com

:( "Despite the claims that the book is aimed at applications, there are few real examples. In the case of noise modeling and noise filtering there are none."

:) "It has the only clear exposition of 2-D non-separable and a trous wavelet methods that I have found anywhere."

Number of techniques have been developed in recent years for the analysis of digital data, especially the manipulation of images. This book provides an in-depth introduction to a range of these data-processing techniques. It develops the reader's understanding of each technique and then shows with practical examples how they can be applied to improve the skills of graduate students and researchers in astronomy, electrical engineering, physics, geophysics and medical imaging.

What sets this book apart from others on the subject is the complementary blend of theory and practical application. Throughout, the book is illustrated with real-world examples from astronomy, electrical engineering, remote sensing and medicine. It also shows how many, more traditional, methods can be enhanced by incorporating the wavelet and multiscale methods into the processing.

For graduate students and researchers already experienced in image processing and data analysis, this book provides a guide to a wide range of data-analysis techniques.

Review(s):

Amazon.com

:( "Despite the claims that the book is aimed at applications, there are few real examples. In the case of noise modeling and noise filtering there are none."

:) "It has the only clear exposition of 2-D non-separable and a trous wavelet methods that I have found anywhere."

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About The Author(s)

Albert Bijaoui is a senior astronomer at the Observatoire de la Côte d'Azur. His scientific activities have revolved around data analysis in astronomy. He was previously involved in several Gaia working groups (imaging, radial velocity spectrometer). Now, he participates in CU8: Astrophysical Parameters. Albert is also the Scientist in Charge for the Observatoire de la Côte d'Azur within the ELSA (European Leadership in Astrometry) programme.

Fionn D. Murtagh is Professor of Data Science, and Director, Centre for Mathematics and Data Science, University of Huddersfield. He was formerly Professor of Data Science, Big Data Lab, Department of Computing and Mathematics, University of Derby and Visiting Professor of Data Science, Department of Computing, Goldsmiths University of London. His research includes digital content analytics; computational science, high performance search and discovery in massive, high dimensional information spaces, and image and signal processing.

Jean-Luc Starck is Director of Research and head of the CosmoStat laboratory at the Institute of Research into the Fundamental Laws of the Universe, Service d'Astrophysique, CEA-Saclay, France. Jean-Luc Starck has a Ph.D from Nice Observatory and an Habilitation from University Paris XI. He was a visitor at the European Southern Observatory in 1993, at UCLA in 2004 and at Stanford’s Department of Statistics in 2000 and 2005. Since 1994, he is a tenured researcher at CEA. He created in 2010 the CosmoStat laboratory and is strongly involved in the Euclid ESA space mission. He received the EADS prize of the French Academy of Science in 2011.

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