HYPERSPECTRAL DATA EXPLOITATION

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1 HYPERSPECTRAL DATA EXPLOITATION

2

3 HYPERSPECTRAL DATA EXPLOITATION THEORY AND APPLICATIONS Edited by CHEIN-I CHANG, PhD University of Maryland Baltimore County Baltimore, MD WILEY-INTERSCIENCE A JOHN WILEY & SONS, INC., PUBLICATION

4 Copyright ß 2007 by John Wiley & Sons, Inc. All rights reserved. Published by John Wiley & Sons, Inc., Hoboken, New Jersey. Published simultaneously in Canada. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning or otherwise, except as permitted under Sections 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, , fax , or on the web at Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) , fax (201) Limit of Liability/Disclaimer of Warranty: While the publisher and author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. For general information on our other products and services please contact our Customer Care Department within the U.S. at , outside the U.S. at or fax Wiley also publishes its books in a variety of electronic formats. Some content that appears in print, however, may not be available in electronic format. Wiley Bicentennial Logo: Richard J. Pacifico Library of Congress Cataloging-in-Publication Data: Hyperspectral data exploitation : theory and applications / edited by Chein-I Chang. p. cm. Includes index. ISBN: (cloth) 1. Remote sensing. 2. Multispectral photography. 3. Image processing Digital techniques. I. Chang, Chein-I. G70.4.H dc Printed in the United States of America

5 CONTENTS PREFACE CONTRIBUTORS vii ix 1. OVERVIEW 1 Chein-I Chang I TUTORIALS 2. HYPERSPECTRAL IMAGING SYSTEMS 19 John P. Kerekes and John R. Schott 3. INFORMATION-PROCESSED MATCHED FILTERS FOR HYPERSPECTRAL TARGET DETECTION AND CLASSIFICATION 47 Chein-I Chang II THEORY 4. AN OPTICAL REAL-TIME ADAPTIVE SPECTRAL IDENTIFICATION SYSTEM (ORASIS) 77 Jeffrey H. Bowles and David B. Gillis 5. STOCHASTIC MIXTURE MODELING 107 Michael T. Eismann and David W. J. Stein 6. UNMIXING HYPERSPECTRAL DATA: INDEPENDENT AND DEPENDENT COMPONENT ANALYSIS 149 Jose M. P. Nascimento and Jose M.B. Dias v

6 vi CONTENTS 7. MAXIMUM VOLUME TRANSFORM FOR ENDMEMBER SPECTRA DETERMINATION 179 Michael E. Winter 8. HYPERSPECTRAL DATA REPRESENTATION 205 Xiuping Jia and John A. Richards 9. OPTIMAL BAND SELECTION AND UTILITY EVALUATION FOR SPECTRAL SYSTEMS 227 Sylvia S. Shen 10. FEATURE REDUCTION FOR CLASSIFICATION PURPOSE 245 Sebastiano B. Serpico, Gabriele Moser, and Andrea F. Cattoni 11. SEMISUPERVISED SUPPORT VECTOR MACHINES FOR CLASSIFICATION OF HYPERSPECTRAL REMOTE SENSING IMAGES 275 Lorenzo Bruzzone, Mingmin Chi, and Mattia Marconcini III APPLICATIONS 12. DECISION FUSION FOR HYPERSPECTRAL CLASSIFICATION 315 Mathieu Fauvel, Jocelyn Chanussot, and Jon Atli Benediktsson 13. MORPHOLOGICAL HYPERSPECTRAL IMAGE CLASSIFICATION: A PARALLEL PROCESSING PERSPECTIVE 353 Antonio J. Plaza 14. THREE-DIMENSIONAL WAVELET-BASED COMPRESSION OF HYPERSPECTRAL IMAGERY 379 James E. Fowler and Justin T. Rucker INDEX 409

7 PREFACE Hyperspectral imaging has become one of most promising and emerging techniques in remote sensing. It has made great advance in recent years due to introduction of new techniques from versatile disciplines, particularly statistical signal processing from engineering aspects. Such clear evidence can be witnessed by hundreds of articles published in journals and conference proceedings every year as well as many annual conferences held in various venues. The rapid growth in this subject has made many researchers difficult to keep up with new developments and advances in its technology. Despite the fact that many books have been published in the area of remote sensing image processing, most have been focused on multispectral image processing rather than hyperspectral signal/image processing. Until recently, only a few appeared as book forms in this particular field. One example is my first book, Hyperspectral Imaging: Spectral Techniques for Detection and Classification, published in 2003 by Kluwer/Plenum Academic Publishers (now part of Springer-Verlag Publishers); this was primarily written for subpixel detection and mixed pixel classification that were designed and developed in my laboratory. Unfortunately, many other topics are also of interest, but were not covered in this particular book. In order to address this need, I have made a significant effort to invite experts in hyperspectral imaging from academia and industries to write chapters in their expertise and share their research works with readers. This book is essentially a result of their contributions. A total of 13 chapters (Chapters 2 to 14) are included in this book and cover a wide spectrum of topics in hyperspectral data exploitation including imaging systems, data modeling, data representation, band selection and partition, and classification to data compression. Each chapter has been contributed by an expert in his/her specialty or by experts in their specialties. Also included is Chapter 1, an overview written by me which provides readers with a discussion on design philosophy in developing hyperspectral imaging techniques from a hyperspectral imagery point of view as well as brief reviews of each of the 13 chapters including coherent connections among different chapters. Therefore, this chapter can serve as a guide to direct readers to particular topics in which they are interested. The ultimate goal of this book is to offer readers a peek at the cutting-edge research in hyperspectral data exploitation. In particular, this book can be found vii

8 viii PREFACE very useful for practitioners and engineers who are interested in this area. It is hoped that the chapters presented in this book have just done that. Last but not least, I would like to thank all contributors for their participation in this book project. I owe them a great debt of gratitude for their efforts which make this book possible. This book would not have been possible without their contributions. CHEIN-I CHANG University of Maryland, Baltimore County December 2006

9 CONTRIBUTORS JON ATLI BENEDIKTSSON, Department of Electrical and Computer Engineering, University of Iceland, 107 Reykjavik, Iceland JEFFERY H. BOWLES, Remote Sensing Division, Naval Research Laboratory, Washington, DC LORENZO BRUZZONE, Department of Information and Communication Technology, University of Trento, I Trento, Italy ANDREA F. CATTONI, Department of Biophysical and Electronic Engineering, University of Genoa, I Genoa, Italy CHEIN-I CHANG, Remote Sensing Signal and Image Processing Laboratory, Department of Computer Science and Electrical Engineering, University of Maryland Baltimore Country, Baltimore, MD JOCELYN CHANUSSOT, Laboratoire des Images et des Signaux, Saint Martin d Heres, France MINGMIN CHI, Department of Information and Communication Technology, University of Trento, I Trento, Italy JOSÉ M. B. DIAS, Instituto de Telecomunicações, Lisbon , Portugal MICHAEL T. EISMANN, AFRL s Sensors Directorate, Electro Optical Technology Division, Electro Optical Targeting Branch, Wright-Patterson AFB, OH MATHIEU FAUVEL, Laboratoire des Images et des Signaux, Saint Martin d Heres, France; and Department of Electrical and Computer Engineering, University of Iceland, 107 Reykjavik, Iceland JAMES E. FOWLER, Department of Electrical and Computer Engineering, Geo- Resources Institute, Mississippi State University, Mississippi State, MS DAVID B. GILLIS, Remote Sensing Division, Naval Research Laboratory, Washington, DC Xiuping. JIA, School of Information Technology and Electrical Engineering, University College, The University of New South Wales, Australian Defense Force Academy, Campbell ACT 2600, Australia JOHN P. KEREKES, Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY MATTIA MARCONCINI, Department of Information and Communication Technology, University of Trento, I Trento, Italy ix

10 x CONTRIBUTORS GABRIELE MOSER, Department of Biophysical and Electronic Engineering, University of Genoa, I Genoa, Italy JOSÉ M. P. NASCIMENTO, Instituto Superior de Engenharia de Lisboa, Lisbon , Portugal ANTONIO J. PLAZA, Department of Computer Science, University of Extremadura, E Caceres, Spain JOHN A. RICHARDS, College of Engineering and Computer Science, The Australian National University, Canberra ACT 0200, Australia JUSTIN T. RUCKER, Department of Electrical and Computer Engineering, Geo- Resources Institute, Mississippi State University, Mississippi State, MS JOHN R. SCHOTT, Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY SEBASTIANO B. SERPICO, Department of Biophysical and Electronic Engineering, University of Genoa, I Genoa, Italy SYLVIA S. SHEN, The Aerospace Corporation, Chantilly, VA, USA DAVID W. J. STEIN, MIT Lincoln Laboratory, Lexington, MA MICHAEL E. WINTER, Hawaii Institute of Geophysics and Planetology, University of Hawaii, Honolulu, HI 96822

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