Introductory digital image processing: a remote sensing perspective

Cover......Page 1
Title Page......Page 4
Copyright Page......Page 5
Brief Contents......Page 6
Contents......Page 7
Preface......Page 27
Acknowledgements......Page 30
About the Author......Page 32
 In Situ Data Collection......Page 34
 Remote Sensing Data Collection......Page 36
  Observations About Remote Sensing......Page 37
  Remote Sensing Advantages and Limitations......Page 40
  Statement of the Problem......Page 41
  Identification of In situ and Remote Sensing Data Requirements......Page 42
  Remote Sensing Data Collection......Page 43
  Remote Sensing Data Analysis......Page 56
  Information Presentation......Page 60
 Earth Observation Economics......Page 61
 Remote Sensing/Digital Image Processing Careers in the Public and Private Sectors......Page 62
 Earth Resource Analysis Perspective......Page 63
 References......Page 65
  Digital Image Terminology......Page 70
  Microdensitometer Digitization......Page 71
  Linear and Area Array Charge-Coupled-Device Digitization......Page 73
  Digitized National Aerial Photography Program (NAPP) Data......Page 75
 Digital Remote Sensor Data Collection......Page 77
  Earth Resource Technology Satellites and Landsat 1-7 Sensor Systems......Page 81
  NOAA Multispectral Scanner Sensors......Page 96
  SeaStar Satellite and Sea-viewing Wide Field-of-view Sensor (SeaWiFS)......Page 103
  NASA Earth Observing-1 (EO-1) Advanced Land Imager (ALI)......Page 106
  NASA Landsat 8 (LDCM - Landsat Data Continuity Mission)......Page 108
  SPOT Sensor Systems......Page 109
  Pleiades......Page 114
  Indian Remote Sensing Systems......Page 115
  Korean Aerospace Research Institute (KARI) KOMPSATs......Page 118
  Astrium, Inc. Sentinel-2......Page 120
  Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)......Page 121
  Multiangle Imaging Spectroradiometer (MISR)......Page 122
  GeoEye, Inc. (formerly Space Imaging, Inc.), IKONOS-2, GeoEye-1, GeoEye-2......Page 123
  EarthWatch/DigitalGlobe, Inc., QuickBird, WorldView-1, WorldView-2, WorldView-3......Page 124
  ImageSat International, Inc., EROS A and EROS B......Page 125
  DMC International Imaging, Ltd., SLIM-6 and NigeriaSat-2......Page 126
 Imaging Spectrometry Using Linear and Area Arrays......Page 127
  NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS)......Page 129
  Moderate Resolution Imaging Spectrometer (MODIS)......Page 130
  NASA Hyperspectral Infrared Imager (HyspIRI)......Page 131
  Itres, Inc. Compact Airborne Spectrographic Imager-1500......Page 132
  HyVista, Inc., HyMap......Page 133
  Small-Format Digital Cameras......Page 134
  Large-Format Digital Cameras......Page 135
  Digital Oblique Aerial Photography......Page 138
  U.S. Space Shuttle Photography......Page 139
 References......Page 141
 Digital Image Processing Hardware Considerations......Page 144
  Central Processing Unit Considerations......Page 145
  Type of Computer......Page 148
  Mode of Operation......Page 149
  Interactive Graphical User Interface......Page 152
 Computer Operating System and Compiler(s)......Page 153
  Output Devices......Page 154
  Rapid Access Mass Storage......Page 155
  Computer Screen Display Resolution......Page 156
 Digital Image Processing Software Considerations......Page 158
  Digital Image Processing Software......Page 159
  Cost......Page 162
 References......Page 163
 Image Processing Mathematical Notation......Page 164
  Types of Sampling......Page 165
 The Histogram and its Significance to Digital Image Processing......Page 166
 Metadata......Page 167
  Cursor Evaluation of Individual Pixel Brightness Values......Page 170
  Measures of Dispersion......Page 171
 Multivariate Image Statistics......Page 174
  Correlation between Multiple Bands of Remotely Sensed Data......Page 175
 Geostatistical Analysis, Autocorrelation and Kriging Interpolation......Page 178
  Empirical Semivariogram......Page 181
 References......Page 184
 Image Display Considerations......Page 186
  Line Printer/Plotter Brightness Maps......Page 187
 Temporary Video Image Display......Page 189
  Bitmapped Graphics......Page 190
  Color Look-Up Tables: 8-bit......Page 193
  Color Composites......Page 197
 Merging (Fusing) Remotely Sensed Data......Page 200
  Color Space Transformation and Component Substitution......Page 202
  Principal Component Analysis (PCA), Independent Component Analysis (ICA), or Gram-Schmidt Substitution......Page 206
  Smoothing Filter-Based Intensity Modulation Image Fusion......Page 208
  Linear Distance Measurement Based on the Pythagorean Theorem......Page 209
  Manhattan Distance Measurement......Page 210
  Perimeter Measurement......Page 212
  Area Measurement......Page 213
 References......Page 214
 Overview......Page 218
 Conduction, Convection, and Radiation......Page 219
  Wave Model of Electromagnetic Energy......Page 220
  The Particle Model: Radiation from Atomic Structures......Page 224
  Refraction......Page 229
  Scattering......Page 230
  Absorption......Page 231
  Reflectance......Page 233
 Terrain Energy–Matter Interactions......Page 234
  Hemispherical Reflectance, Absorptance, and Transmittance......Page 235
  Radiant Flux Density......Page 236
 Energy-Matter Interactions at the Sensor System......Page 237
  Line or Column Drop-Outs......Page 238
  N-Line Striping......Page 240
  Unnecessary Atmospheric Correction......Page 241
  Necessary Atmospheric Correction......Page 244
  Absolute Radiometric Correction of Atmospheric Attenuation......Page 245
  Relative Radiometric Correction of Atmospheric Attenuation......Page 256
  The Cosine Correction......Page 263
  The C Correction......Page 264
 References......Page 265
  Internal Geometric Error......Page 268
  External Geometric Error......Page 273
  Image-to-Map Rectification......Page 275
  Hybrid Approach to Image Rectification/Registration......Page 276
  Image-to-Map Geometric Rectification Logic......Page 277
  Selecting an Appropriate Map Projection......Page 285
  Determine Optimum Geometric Rectification Coefficients by Evaluating GCP Total RMSerror......Page 296
  Mosaicking Rectified Images......Page 300
 References......Page 304
  Image Reduction......Page 306
  Image Magnification......Page 307
 Transects (Spatial Profiles)......Page 308
 Spectral Profiles......Page 312
  Linear Contrast Enhancement......Page 315
  Nonlinear Contrast Enhancement......Page 319
 Band Ratioing......Page 321
 Neighborhood Raster Operations......Page 324
  Spatial Convolution Filtering......Page 326
  The Fourier Transform......Page 335
 Principal Components Analysis (PCA)......Page 341
 Vegetation Indices (VI)......Page 347
  Dominant Factors Controlling Leaf Reflectance......Page 349
  Remote Sensing-Derived Vegetation Indices......Page 358
  First-Order Statistics in the Spatial Domain......Page 373
  Second-Order Statistics in the Spatial Domain......Page 378
  Texture Units as Elements of a Texture Spectrum......Page 381
  Texture Statistics Based on the Semi-variogram......Page 382
 Landscape Ecology Metrics......Page 383
 References......Page 386
 Introduction......Page 394
 Supervised Classification......Page 395
  Land-Use and Land-Cover Classification Schemes......Page 397
  Training Site Selection and Statistics Extraction......Page 409
  Selecting the Optimum Bands for Image Classification: Feature Selection......Page 415
  Select the Appropriate Classification Algorithm......Page 426
  Unsupervised Classification Using the Chain Method......Page 435
  Unsupervised Classification Using the ISODATA Method......Page 439
 Fuzzy Classification......Page 445
 Object-Based Image Analysis (OBIA) Classification......Page 446
  Geographic Object-Based Image Analysis and Classification......Page 447
  OBIA Classification Considerations......Page 453
 Incorporating Ancillary Data in the Classification Process......Page 454
  Approaches to Incorporating Ancillary Data to Improve Remote Sensing Classification Maps......Page 455
 References......Page 456
10. Information Extraction Using Artificial Intelligence......Page 462
  Creating the Knowledge Base......Page 463
  Inference Engine......Page 467
 Decision-Tree Classification Based on Human-Derived Rules......Page 468
 Classification Based on Machine Learning Decision Trees and Regression Trees......Page 469
  Machine Learning......Page 471
  From Decision Trees to Production Rules......Page 474
 Support Vector Machines......Page 477
 Neural Networks......Page 478
  Components and Characteristics of a Typical Artificial Neural Network Used to Extract Information from Remotely Sensed Data......Page 479
  Advantages of Artificial Neural Networks......Page 484
 References......Page 486
  Panchromatic......Page 492
  Hyperspectral......Page 493
 Steps to Extract Information from Hyperspectral Data......Page 495
  Animation......Page 498
 Radiometric Calibration......Page 500
  In Situ Data Collection......Page 501
  Absolute Atmospheric Correction......Page 502
 Geometric Correction of Hyperspectral Remote Sensor Data......Page 504
  Minimum Noise Fraction (MNF) Transformation......Page 505
 Endmember Determination: Locating the Spectrally Purest Pixels......Page 507
  n-Dimensional Endmember Visualization......Page 508
  Spectral Angle Mapper......Page 512
  Subpixel Classification, Linear Spectral Unmixing or Spectral Mixture Analysis......Page 513
  Spectroscopic Library Matching Techniques......Page 517
  Machine Learning Analysis of Hyperspectral Data......Page 520
 Selected Indices Useful for Hyperspectral Data Analysis......Page 524
  Physiological Reflectance Index—PRI......Page 525
  Linear Red-Edge Position—REP......Page 526
 Derivative Spectroscopy......Page 527
  Narrow-Band Derivative-Based Vegetation Indices......Page 528
 References......Page 529
  Specify the Change Detection Geographic Region of Interest (ROI)......Page 534
  Select Hard (Crisp) and/or Soft (Fuzzy) Change Detection Logic......Page 535
  Remote Sensing System Change Detection Considerations......Page 537
  Environmental/Developmental Considerations of Importance When Performing Change Detection......Page 539
  Select the Most Appropriate Change Detection Algorithm......Page 545
  Analog “On-Screen” Visualization Change Detection......Page 547
  Binary Change Detection Using Image Algebra......Page 551
  Multiple-Date Composite Image Change Detection......Page 556
  Photogrammetric Change Detection......Page 562
  LiDARgrammetric Change Detection......Page 564
  Post-Classification Comparison Change Detection......Page 565
  Neighborhood Correlation Image (NCI) Change Detection......Page 571
  Spectral Change Vector Analysis......Page 575
  Change Detection Using an Ancillary Data Source as Date 1......Page 576
  Change Detection Using a Binary Change Mask Applied to Date 2......Page 577
  Cross-Correlation Change Detection......Page 578
  Visual On-Screen Change Detection and Digitization......Page 579
  When Atmospheric Correction Is Necessary......Page 581
 References......Page 584
 Steps to Perform Accuracy Assessment......Page 590
 Sources of Error in Remote Sensing–Derived Thematic Maps......Page 591
 The Error Matrix......Page 594
 Training versus Ground Reference Test Information......Page 595
  Sample Size Based on Multinomial Distribution......Page 596
 Sampling Design (Scheme)......Page 597
  Simple Random Sampling......Page 598
  Stratified Random Sampling......Page 599
  Cluster Sampling......Page 600
 Obtaining Ground Reference Information at Locations Using a Response Design......Page 601
  Descriptive Evaluation of Error Matrices......Page 602
  Discrete Multivariate Techniques Applied to the Error Matrix......Page 603
  Fuzzification of the Error Matrix......Page 604
 Change Detection Map Accuracy Assessment......Page 608
  Assessing the Accuracy of a “From-To” Change Detection Map......Page 609
  Assessing the Accuracy of a Binary Change Detection Map......Page 610
 Geostatistical Analysis in Support of Accuracy Assessment......Page 611
  Lineage of Remote Sensing–Derived Products......Page 612
 References......Page 613
  Hydrography Data......Page 616
  USGS EarthExplorer......Page 617
  USGS The National Map......Page 618
  USGS Global Visualization Viewer......Page 619
  Google, Inc., Google earth Search Engine......Page 620
  Microsoft, Inc., bing Search Engine......Page 621
  Esri, Inc., ArcGIS Online Map and Geoservices......Page 622
 Digital Elevation Data......Page 624
  SRTM—Shuttle RADAR Topography Mission......Page 625
 Land Use/Land Cover and Biodiversity/Habitat Data......Page 626
  EDNA—Elevation Derivatives for National Applications......Page 627
  NWI—National Wetlands Inventory......Page 628
 Remote Sensor Data—Commercial and International......Page 629
  LandScan Population Distribution Modeling......Page 630
  Declassified Satellite Imagery......Page 631
  MODIS—Moderate Resolution Imaging Spectrometer......Page 632
  EROS A and B......Page 633
  PICTOMETRY......Page 634
  WorldView–1, –2, and –3......Page 635
Index......Page 636
Back Cover......Page 658