LEADER 05328nam 2200661Ia 450 001 9910830861503321 005 20230617031011.0 010 $a1-280-27329-1 010 $a9786610273294 010 $a0-470-32133-4 010 $a0-471-72125-5 010 $a0-471-72380-0 035 $a(CKB)1000000000019040 035 $a(EBL)224925 035 $a(OCoLC)475932073 035 $a(SSID)ssj0000245829 035 $a(PQKBManifestationID)11237211 035 $a(PQKBTitleCode)TC0000245829 035 $a(PQKBWorkID)10180213 035 $a(PQKB)10929872 035 $a(MiAaPQ)EBC224925 035 $a(EXLCZ)991000000000019040 100 $a20040422d2003 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aSignal theory methods in multispectral remote sensing$b[electronic resource] /$fDavid A. Landgrebe 210 $aHoboken, N.J. $cWiley$dc2003 215 $a1 online resource (530 p.) 225 1 $aWiley series in remote sensing 300 $aDescription based upon print version of record. 311 $a0-471-42028-X 320 $aIncludes bibliographical references and index. 327 $aSIGNAL THEORY METHODS IN MULTISPECTRAL REMOTE SENSING; Contents; PREFACE; PART I. INTRODUCTION; CHAPTER 1. INTRODUCTION AND BACKGROUND; 1.1 THE BEGINNING OF SPACE AGE REMOTE SENSING; 1.2 THE FUNDAMENTAL BASIS FOR REMOTE SENSING; 1.3 THE SYSTEMS VIEW AND ITS INTERDISCIPLINARY NATURE; 1.4 THE EM SPECTRUM AND HOW INFORMATION IS CONVEYED; 1.5 THE MULTISPECTRAL CONCEPT AND DATA REPRESENTATIONS; 1.6 DATA ANALYSIS AND PARTITIONING FEATURE SPACE; 1.7 THE SIGNIFICANCE OF SECOND-ORDER VARIATIONS; 1.8 SUMMARY; PART II. THE BASICS FOR CONVENTIONAL MULTISPECTRAL DATA 327 $aCHAPTER 2. RADIATION AND SENSOR SYSTEMS IN REMOTE SENSING2.0 INTRODUCTION; 2.1 RADIATION TERMINOLOGY AND UNITS; 2.2 PLANCK'S LAW AND BLACK BODY RADIATION; 2.3 SOLAR RADIATION; 2.4 ATMOSPHERIC EFFECTS; 2.5 SENSOR OPTICS; 2.6 DESCRIBING SURFACE REFLECTANCE; 2.7 RADIATION DETECTORS; 2.8. SORTING RADIATION BY WAVELENGTH; 2.9 MULTISPECTRAL SENSOR SYSTEMS; 2.10 THE DEVELOPMENT OF MULTISPECTRAL SENSOR SYSTEMS; 2.11 SUMMARY; CHAPTER 3. PATTERN RECOGNITION IN REMOTE SENSING; 3.1 THE SYNOPTIC VIEW AND THE VOLUME OF DATA; 3.2 WHAT IS A PATTERN?; 3.3 DISCRIMINANT FUNCTIONS 327 $a3.4 TRAINING THE CLASSIFIER: AN ITERATIVE APPROACH3.5 TRAINING THE CLASSIFIER: THE STATISTICAL APPROACH; 3.6 DISCRIMINANT FUNCTIONS: THE CONTINUOUS CASE; 3.7 THE GAUSSIAN CASE; 3.8 OTHER TYPES OF CLASSIFIERS; 3.9 THRESHOLDING; 3.10 ON THE CHARACTERISTICS, VALUE, AND VALIDITY OF THE GAUSSIAN ASSUMPTION; 3.11 THE HUGHES EFFECT; 3.12 SUMMARY TO THIS POINT; 3.13 EVALUATING THE CLASSIFIER: PROBABILITY OF ERROR; 3.14 CLUSTERING: UNSUPERVISED ANALYSIS; 3.15 THE NATURE OF MULTISPECTRAL DATA IN FEATURE SPACE; 3.16 ANALYZING DATA: PUTTING THE PIECES TOGETHER; 3.17 AN EXAMPLE ANALYSIS 327 $aPART III. ADDITIONAL DETAILSCHAPTER 4. TRAINING A CLASSIFIER; 4.1 CLASSIFIER TRAINING FUNDAMENTALS; 4.2 THE STATISTICS ENHANCEMENT CONCEPT; 4.3 THE STATISTICS ENHANCEMENT IMPLEMENTATION; 4.4 ILLUSTRATIONS OF THE EFFECT OF STATISTICS ENHANCEMENT; 4.5 ROBUST STATISTICS ENHANCEMENT; 4.6 ILLUSTRATIVE EXAMPLES OF ROBUST EXPECTATION MAXIMATION; 4.7 SOME ADDITIONAL COMMENTS; 4.8 A SMALL SAMPLE COVARIANCE ESTIMATION SCHEME; 4.9 RESULTS FOR SOME EXAMPLES; CHAPTER 5. HYPERSPECTRAL DATA CHARACTERISTICS; 5.1 INTRODUCTION; 5.2 A VISUALIZATION TOOL; 5.3 ACCURACY VS. STATISTICS ORDER 327 $a5.4 HIGH-DIMENSIONAL SPACES: A CLOSER LOOK5.5 ASYMPTOTICAL FIRST AND SECOND ORDER STATISTICS PROPERTIES; 5.6 HIGH-DIMENSIONAL IMPLICATIONS FOR SUPERVISED CLASSIFICATION; CHAPTER 6. FEATURE DEFINITION; 6.1 INTRODUCTION; 6.2 AD HOC AND DETERMINISTIC METHODS; 6.3 FEATURE SELECTION; 6.4 PRINCIPAL COMPONENTS/KARHUNEN-LOEVE; 6.5 DISCRIMINANT ANALYSIS FEATURE EXTRACTION (DAFE); 6.6 DECISION BOUNDARY FEATURE EXTRACTION (DBFE); 6.7 NONPARAMETRIC WEIGHTED FEATURE EXTRACTION (NWFE); 6.8 PROJECTION PURSUIT; CHAPTER 7. A DATA ANALYSIS PARADIGM AND EXAMPLES 327 $a7.1 A PARADIGM FOR MULTISPECTRAL AND HYPERSPECTRAL DATA ANALYSIS 330 $aAn outgrowth of the author's extensive experience teaching senior and graduate level students, this is both a thorough introduction and a solid professional reference.* Material covered has been developed based on a 35-year research program associated with such systems as the Landsat satellite program and later satellite and aircraft programs.* Covers existing aircraft and satellite programs and several future programs *An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department. 410 0$aWiley series in remote sensing. 606 $aRemote sensing 606 $aMultispectral photography 606 $aSignal theory (Telecommunication) 615 0$aRemote sensing. 615 0$aMultispectral photography. 615 0$aSignal theory (Telecommunication) 676 $a621.3678 700 $aLandgrebe$b D. A$0151005 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830861503321 996 $aSignal theory methods in multispectral remote sensing$93067562 997 $aUNINA