1.

Record Nr.

UNINA9910841237503321

Autore

Landgrebe D. A

Titolo

Signal theory methods in multispectral remote sensing / / David A. Landgrebe

Pubbl/distr/stampa

Hoboken, N.J., : Wiley, c2003

ISBN

1-280-27329-1

9786610273294

0-470-32133-4

0-471-72125-5

0-471-72380-0

Descrizione fisica

1 online resource (530 p.)

Collana

Wiley series in remote sensing

Disciplina

621.3678

Soggetti

Remote sensing

Multispectral photography

Signal theory (Telecommunication)

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

SIGNAL 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

CHAPTER 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

3.4 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

PART 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

5.4 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

7.1 A PARADIGM FOR MULTISPECTRAL AND HYPERSPECTRAL DATA ANALYSIS

Sommario/riassunto

An 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.