Signal and Image Processing for Remote Sensing

C.H. Chen

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English

CRC Press
30 September 2020

Communications engineering & telecommunications; Applied optics; Signal processing

Series: Signal and Image Processing of Earth Observations

"Continuing in the footsteps of the pioneering first edition, Signal and Image Processing for Remote Sensing, Second Edition explores the most up-to-date signal and image processing methods for dealing with remote sensing problems. Although most data from satellites are in image form, signal processing can contribute significantly in extracting information from remotely sensed waveforms or time series data. This book combines both, providing a unique balance between the role of signal processing and image processing.

Featuring contributions from worldwide experts, this book continues to emphasize mathematical approaches. Not limited to satellite data, it also considers signals and images from hydroacoustic, seismic, microwave, and other sensors. Chapters cover important topics in signal and image processing and discuss techniques for dealing with remote sensing problems. Each chapter offers an introduction to the topic before delving into research results, making the book accessible to a broad audience.

This second edition reflects the considerable advances that have occurred in the field, with 23 of 27 chapters being new or entirely rewritten. Coverage includes new mathematical developments such as compressive sensing, empirical mode decomposition, and sparse representation, as well as new component analysis methods such as non-negative matrix and tensor factorization. The book also presents new experimental results on SAR and hyperspectral image processing.

The emphasis is on mathematical techniques that will far outlast the rapidly changing sensor, software, and hardware technologies. Written for industrial and academic researchers and graduate students alike, this book helps readers connect the ""dots"" in image and signal processing.

New in This Edition

The second edition includes four chapters from the first edition, plus 23 new or entirely rewritten chapters, and 190 new figures. New"

By: C.H. Chen
Imprint: CRC Press
Country of Publication: United Kingdom
Edition: 2nd edition
Dimensions: Height: 254mm, Width: 178mm,
Weight: 453g
ISBN: 9780367866143
ISBN 10: 0367866145
Series: Signal and Image Processing of Earth Observations
Pages: 619
Publication Date: 30 September 2020
Audience: College/higher education , Primary
Format: Paperback
Publisher's Status: Active

Chi Hau Chen is currently the Chancellor Professor Emeritus of electrical and computer engineering at the University of Massachusetts Dartmouth, where he has taught since 1968. Dr. Chen has published 29 books in his areas of research. He served as associate editor of the IEEE Transactions on Acoustics, Speech and Signal Processing for four years, associate editor of the IEEE Transactions on Geoscience and Remote Sensing for 15 years, and since 2008 has been a board member of Pattern Recognition. Dr. Chen is a Life Fellow of the IEEE, a Fellow of the International Association of Pattern Recognition (IAPR), and a member of Academia NDT International. For more information about Dr. Chen, visit his web page at the University of Massachusetts Dartmouth.

Reviews for Signal and Image Processing for Remote Sensing

Praise for the First Edition ...this book will be useful to advance automated image processing and the integration of remote sensor data with ecosystem and atmospheric models. The unique idea of combining signal processing with image processing is a good one and is well timed with ongoing technological advancements. —Ross Lunetta, co-editor of Remote Sensing Change Detection and Remote Sensing and GIS Accuracy Assessment Overall, the breadth and depth of content make this book an excellent reference for researchers, including graduate students, engaged in advanced remote sensing data analysis, who will find that some chapters provide inspiration to their own research. —Qian Du, Department of Electrical and Computer Engineering, Mississippi State University, in Photogrammetric Engineering & Remote Sensing, Nov. 2007, Vol. 73, No. 11