Digital photogrammetry: Volume 1 Background, fundamentals automatic orientation procedures
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| Main Author: | |
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| Format: | Book |
| Language: | English |
| Published: |
Laurelville, OH
TerraScience
1999
|
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | 422 S. Ill., graf. Darst. |
| ISBN: | 0967765307 0967765315 |
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MARC
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| 245 | 1 | 0 | |a Digital photogrammetry |n Volume 1 |p Background, fundamentals automatic orientation procedures |c Toni Schenk |
| 264 | 1 | |a Laurelville, OH |b TerraScience |c 1999 | |
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| adam_text | Titel: Bd. 1. Digital photogrammetry. Background, fundamentals, automatic orientation procedures
Autor: Schenk, Toni
Jahr: 1999
Contents
1 Introduction 1
1.1 Background............................... 1
1.2 Terminology—Or the Lack Thereof................. 3
1.3 Generic Digital Photogrammetry Environment.......... 4
1.4 Properties of Digital Imagery.................... 5
1.4.1 Definition of Digital Image.................. 5
1.4.2 Spatial Resolution and Geometric Accuracy....... 6
1.4.3 Radiometrie Resolution ................... 8
1.5 Classification of Processes and Tasks in Digital Photogrammetry 8
1.5.1 System Level Tasks...................... 9
1.5.2 Low Level Tasks........................ 9
1.5.3 Middle Level Tasks...................... 10
1.5.4 High Level Tasks........................ 10
1.6 Relationship of Digital Photogrammetry To Other Disciplines 10
1.7 A View of Things to Come...................... 12
1 Background 15
2 Digital Signal Processing 17
2.1 Signals and Systems.......................... 17
2.1.1 Sequences............................ 18
Operations on Sequences.................. 18
Examples of Sequences.................... 19
2.1.2 Linear Shift-Invariant Systems ............... 19
Linearity............................. 20
Shift-Invariance ........................ 21
Stability............................. 23
Causality............................ 23
Inverübility........................... 24
2.2 Frequency Representation...................... 24
x¡¡ CONTENTS
2.3 Fourier Transforms.......................... 26
2.3.1 Fourier Integral ........................ 27
Theorems............................ 28
Some Transform Pairs.................... 29
Discrete Fourier Transform................. 31
2.3.2 Summary............................ 32
2.4 Digital Filtering............................. 35
2.4.1 Moving Average Filter..................... 35
2.4.2 Ideal Lowpass Filter...................... 37
2.5 To Probe Further............................ 38
Digital Image Processing 41
3.1 Image Models.............................. 42
3.2 Image Characteristics......................... 44
3.2.1 Average and Standard Deviation.............. 44
3.2.2 Entropy............................. 45
3.2.3 Histogram............................ 45
3.2.4 Moments............................. 46
3.3 Image Enhancement and Restoration............... 47
3.3.1 Histogram Modifications................... 49
Contrast Stretching...................... 49
Histogram Equalization ................... 50
3.3.2 Smoothing Operators..................... 51
Averaging Operator...................... 52
Gaussian Filter......................... 53
3.3.3 Sharpening Operators .................... 54
3.3.4 Difference Operators..................... 54
Image Gradient......................... 54
Gradient Image Representation............... 57
Laplace Operator ....................... 57
3.3.5 Image Correction ....................... 59
Median Filter.......................... 60
Eliminating Erroneous Pixels................ 60
Eliminating Erroneous Rows or Columns......... 61
3.4 Geometric Transformations..................... 62
3.4.1 Size of Transformed Image................. 63
3.4.2 Resampling........................... 64
3.5 Image Segmentation.......................... 66
3.5.1 Histogram Thresholding................... 67
3.5.2 Co-Occurrence Matrix..................... 69
3.5.3 Texture Segmentation by Gabor Filters.......... 72
Gabor Functions........................ 73
CONTENTS
Selection of Filter Parameters................ 73
3.6 To Probe Further............................ 75
Human Vision 77
4.1 Overview of Human Visual System................. 77
4.2 The Eye.................................. 80
4.2.1 The Eyeball........................... 80
4.2.2 Optical Properties of the Eye................ 81
Image Formation........................ 81
Resolution............................ 82
4.2.3 Photometric Properties of the Photoreceptors...... 85
Response of Ganglion Cells: Receptive Fields...... 87
4.3 Visual Cortex.............................. 89
4.3.1 Overview............................. 89
4.3.2 Cortical Receptive Fields................... 91
Orientation Sensitive Cells.................. 91
Direction Sensitive Cells................... 91
End-Stopped Cells....................... 91
Binocular Sensitive Cells................... 92
4.4 Visual Perception ........................... 92
4.4.1 Perceptual Organization................... 94
4.4.2 Other Perceptual Processes................. 95
4.5 Marr s Theory about Vision..................... 97
4.5.1 Primal Sketch.......................... 97
4.5.2 2.5-D Sketch .......................... 98
4.5.3 3-D Model Representation.................. 99
4.6 To Probe Further............................ 10°
Computer Vision 101
5.1 Background............................... 10^
5.2 Key Concepts, Key Issues....................... 105
5.2.1 Vision is Modular and Hierarchical ............ 105
5.2.2 Vision is Ill-Posed....................... 106
5.2.3 Transition from Early Vision to Late Vision....... 107
5.3 Edge Detection............................. 108
5.3.1 Detecting Edge Pixels..................... 110
Laplacian of Gaussian (LoG) Edge Operator....... HI
5.3.2 Linking Edge Pixels...................... 114
5.4 Scale-Space Theory and Image Pyramids............. 116
5.4.1 Scale-Space Generation.................... 116
lift
5.4.2 Image Pyramids........................ Ll°
5.5 Perceptual Organization.......................
xiv CONTENTS
5.5.1 Background........................... 12°
5.5.2 Analysis of Blockworld Scenes............... I21
5.5.3 Curvilinear Segmentation.................. 121
Hough Transform....................... 121
Virtual Lines..........................
5.5.4 Region Segmentation.....................
5.5.5 More General Approaches.................. 124
5.6 Object Recognition .......................... 125
5.6.1 Global Model-Based Recognition.............. 126
Matching Geometric Structures............... 126
Matching (/ - s Curves.................... 126
Matching Moment Invariants................ 127
5.6.2 Feature Matching With Geometric Constraints ..... 128
Correspondence Problem.................. 129
Verifying Hypotheses..................... 131
5.6.3 Nonmodel-Based Object Recognition........... 132
5.7 To Probe Further............................ 132
Radiometry and Photometry 135
6.1 Electromagnetic Radiation...................... 135
6.1.1 Wave Characteristic of EMR................. 136
6.1.2 Quantum Nature of Radiation................ 136
6.1.3 Electromagnetic Spectrum.................. 137
6.2 Radiometry............................... 139
6.2.1 Solid Angle........................... 139
6.2.2 Radiometrie Quantities.................... 140
Radiant Energy, Q....................... 140
Radiant Flux, $......................... 140
Radiant Flux Density, E and M ............... 141
Radiant Intensity, I...................... 141
Radiance, L........................... 142
6.2.3 Lambertian Radiators..................... 143
6.2.4 Relationship of Radiometrie Quantities.......... 143
Relationship Between Radiance and Irradiance..... 143
Relationship Between Radiance and Flux......... 144
6.2.5 Thermal Radiation....................... 145
6.2.6 Photon Flux........................... 147
6.3 Photometry............................... 148
6.3.1 Photometric Quantities.................... 148
Luminous Energy, Q ..................... 148
Luminous Flux, i ....................... 148
Luminous Flux Densities, E and M............. 148
CONTENTS xv
Luminous Intensity, /..................... 149
Luminance, L.......................... 149
6.3.2 Relationship Between Radiant and Photometric Quan-
tities ............................... 149
6.4 Radiative Energy Transfer...................... 149
6.4.1 General Case.......................... 150
6.4.2 Radiative Energy Transfer Through Lens System .... 151
Flux Across Aperture..................... 151
Irradiance at Image Plane .................. 152
6.5 To Probe Further............................ 154
II Fundamentals of Digital Photogrammetry 155
7 Electronic Imaging Systems 157
7.1 Introduction............................... 158
7.2 CCD Sensors: Working Principle and Properties......... 160
7.2.1 Working Principle....................... 160
Linear Array With Bilinear Readout............ 163
Frame Transfer......................... 163
Interline Transfer....................... 163
Time-Delay and Integration (TDI) Transfer........ 164
7.2.2 Major Properties........................ 165
Noise............................... 165
Spectral Response....................... 165
Linearity and Dynamic Range................ 167
7.3 Solid-State Cameras.......................... i68
7.3.1 Camera Overview....................... 169
7.3.2 Analog Output......................... 171
7.3.3 Line Cameras.......................... 172
7.3.4 Comparison Between Analog and Digital Cameras ... 177
7.4 Frame Grabbers ............................ 182
7.4.1 Timing Circuitry........................ 183
7.4.2 A/D Converter......................... 183
8 Scanners 189
8.1 Introduction............................... 189
8.2 Drum Scanners vs. Flatbed Scanners ............... 190
8.3 Principal Components of Flatbed Scanners............ 191
8.3.1 Illumination and Optic System............... 191
8.3.2 Photo Carrier.......................... 19^
8.3.3 Sensor..............................
8.3.4 Scanner Electronics......................
xvj CONTENTS
8.3.5 Host Computer......................... 196
8.4 Pixel Size................................. 197
8.4.1 Relationship Between Sensor Pixel and Scanner Pixel . 197
8.4.2 Relationship Between Scanner Pixel and Photo Pixel . . 198
8.5 Potential Error Sources........................ 199
8.5.1 Geometry: Position and Resolution............ 199
8.5.2 Radiometrie Representation................. 200
9 Digital Photogrammetric Workstations 203
9.1 Background............................... 203
9.1.1 Digital Photogrammetric Workstation and Digital Pho-
togrammetry Environment.................. 204
9.1.2 Historical Perspective..................... 205
9.1.3 Current Status......................... 207
9.1.4 Classification of Digital Photogrammetric Workstations 208
9.2 Basic System Components...................... 209
9.3 Basic System Functionality...................... 211
9.3.1 Storage System......................... 211
9.3.2 Viewing and Measuring System............... 213
9.3.3 Stereoscopic Viewing..................... 215
9.3.4 Roaming............................. 218
9.4 Application Functionality ...................... 220
9.4.1 Preparation........................... 221
9.4.2 Orientation Procedures.................... 222
Interior Orientation...................... 222
Relative Orientation...................... 222
Absolute Orientation..................... 223
9.4.3 Digital Aerial Triangulation................. 224
9.4.4 Automatic DEM Generation................. 224
9.4.5 Digital Orthophoto Production............... 225
9.5 .Analytical Plotters vs. DPWs..................... 225
9.6 Summary................................. 227
10 Image Matching Fundamentals 231
10.1 Introduction............................... 231
10.1.1 Historical Remarks...................... 231
10.1.2 Terminology, Working Definitions............. 232
10.1.3 Problem Statement...................... 234
10.2 Fundamental Problems of Image Matching............ 234
10.2.1 Search Space, Uniqueness of Matching Entity...... 234
10.2.2 Approximations, Constraints and Assumptions .... 235
10.2.3 Geometric Distortions of Matching Entities....... 237
CONTENTS xvjj
Geometric Distortion Due to Orientation Parameters . 238
Effect of Tilted Surface on Geometric Distortions . . . 239
Effect of Relief on Geometric Distortions......... 241
10.3 Solutions to the Fundamental Problems ............. 242
10.3.1 Search Space and Approximations............. 242
Epipolar Lines ......................... 242
Vertical line Locus...................... 246
Hierarchical Approach.................... 249
10.3.2 Uniqueness of Matching Entity............... 251
10.4 Area-Based Matching......................... 252
10.4.1 Correlation........................... 254
Cross-Correlation Factor................... 254
Maximum Correlation Factor................ 255
Procedure............................ 257
10.4.2 Least-Squares Matching ................... 257
Mathematical Model...................... 258
Adjustment Procedure.................... 262
11 Advanced Image Matching Methods 267
11.1 Feature-Based Matching ....................... 268
11.1.1 Feature Extraction....................... 268
Interest Points......................... 268
Edge Detection......................... 269
Extracting Regions....................... 269
11.1.2 Matching Interest Points................... 270
11.1.3 Matching Edge Pixels..................... 271
11.1.4Matching Entire Edges .................... 274
tfj - s Approach........................ 2 74
Generalized Hough Transform............... 277
11.2 Relational Matching.......................... 279
11.2.1 Description of Primitives and Relations ......... 281
11.2.2 Evaluation Function...................... 283
11.2.3 Tree Search........................... 284
11.3 Template Matching.......................... 286
11.3.1 Matching Environment.................... 287
11.3.2 Matching Strategy....................... 287
11.3.3 Target Detection........................ 288
Computational Approach.................. 288
Histogram Thresholding................... 289
Cross-Correlation....................... 290
Feature-Based Matching................... 290
11.3.4 Precise Localization...................... 291
CONTENTS
Area-Based Methods ..................... 291
Feature-Based Methods.................... 295
12 Computing Normalized Images 301
12.1 Introduction............................... 302
12.2 Epipolar Geometry........................... 304
12.3 Transformation from Original to Normalized Image...... 305
12.3.1 Transformation Using Collinearity Equations...... 308
12.3.2 Projective Transformation.................. 308
12.4 Normalized Digital Images...................... 309
12.4.1 Definition of Normalized Digital Image.......... 311
III Automatic Orientation Procedures 315
13 Automatic Interior Orientation 319
13.1 Purpose of Interior Orientation................... 319
13.2 Determining Interior Orientation.................. 321
13.2.1 Transformation from Pixel to Image Coordinate System 321
13.2.2 Image Refinement....................... 322
Refraction............................ 323
Camera Imperfections.................... 324
Firm Shrinkage......................... 325
Scanner Errors......................... 325
Image Refinement Using Digital Cameras ........ 326
Summary of Image Refinement............... 327
13.3 Interactive Interior Orientation................... 327
13.4 Autonomous Interior Orientation ................. 329
13.4.1 Background and Motivation................. 330
13.4.2 Objective of Autonomous Interior Orientation..... 331
13.4.3 Assumptions.......................... 331
13.4.4 Approaches to AIO...................... 333
13.4.5 The Anatomy of a Fiducial Mark.............. 334
13.5 Area-Based Approach......................... 335
13.5.1 Precise Localization...................... 339
13.6 Feature-Based Approach....................... 342
13.6.1 Detecting Circles........................ 344
13.6.2 Detecting Straight lines................... 346
13.6.3 Precise Localization...................... 349
13.7 Summary................................. 351
CONTENTS xjx
14 Automatic Relative Orientation 355
14.1 Background............................... 355
14.1.1 Traditional vs. Automatic Orientation.......... 356
14.1.2 Mathematical Models for Relative Orientation...... 357
Collinearity Model....................... 358
Coplanarity Model....................... 360
Linear Models.......................... 362
14.2 Interactive Relative Orientation................... 362
14.3 Automatic Orientation with Interest Points ........... 363
14.3.1 Extracting Interest Points.................. 363
14.3.2 Matching Interest Points................... 364
14.4 Automatic Orientation with Edge Pixels.............. 367
14.4.1 Matching Edges ........................ 367
14.4.2 Computing Orientation Parameters with Characteristic
Edge Points........................... 367
14.5 Automatic Orientation with Edge Entities............. 368
14.5.1 Relevant Edge Characteristics................ 370
Edge Pixels Are Not Necessarily Conjugate........ 370
Ends of Edges are Ill-Defined................ 371
Accuracy of Edge Pixels ................... 371
14.5.2 Computation of the Orientation Parameters....... 372
14.5.3 Computation of the Surface................. 375
14.5.4 Strategy............................. 377
14.6 Computing Orientation Parameters Without Prior Matching . 377
14.6.1 Principle............................. 377
14.6.2 Matching Edges by Trial and Error............. 380
14.7 Summary................................. 382
15 Automatic Exterior Orientation 387
15.1 Direct vs. Indirect Orientation ................... 389
15.2 Background............................... 392
15.2.1 Single Image Resection.................... 392
15.2.2 Absolute Orientation..................... 393
15.2.3 Exterior Orientation Parameters from Relative and Ab-
solute Orientation....................... 39j
15.3 Automatic Orientation with Control Points............ 395
15.3.1 Automatic Detection of Targets.............. 396
15.3.2 Automatic Detection of Topographic Control Points . . 398
15.4 Automatic Orientation with Control Features.......... 399
15.4.1 Matching Extracted Features with Control Features .. 400
15.4.2 Computing Orientation Parameters with Control Lines 403
15.5 Automatic Orientation with Control Surfaces.......... 407
xx CONTENTS
15.5.1 Problem Statement...................... 407
15.5.2 Solution............................. 408
Geometric Considerations.................. 408
Mathematical Model...................... 409
15.5.3 Procedure............................ 411
15.6 Summary................................. 412
Author Index 417
Subject Index 421
|
| adam_txt |
Titel: Bd. 1. Digital photogrammetry. Background, fundamentals, automatic orientation procedures
Autor: Schenk, Toni
Jahr: 1999
Contents
1 Introduction 1
1.1 Background. 1
1.2 Terminology—Or the Lack Thereof. 3
1.3 Generic Digital Photogrammetry Environment. 4
1.4 Properties of Digital Imagery. 5
1.4.1 Definition of Digital Image. 5
1.4.2 Spatial Resolution and Geometric Accuracy. 6
1.4.3 Radiometrie Resolution . 8
1.5 Classification of Processes and Tasks in Digital Photogrammetry 8
1.5.1 System Level Tasks. 9
1.5.2 Low Level Tasks. 9
1.5.3 Middle Level Tasks. 10
1.5.4 High Level Tasks. 10
1.6 Relationship of Digital Photogrammetry To Other Disciplines 10
1.7 A View of Things to Come. 12
1 Background 15
2 Digital Signal Processing 17
2.1 Signals and Systems. 17
2.1.1 Sequences. 18
Operations on Sequences. 18
Examples of Sequences. 19
2.1.2 Linear Shift-Invariant Systems . 19
Linearity. 20
Shift-Invariance . 21
Stability. 23
Causality. 23
Inverübility. 24
2.2 Frequency Representation. 24
x¡¡ CONTENTS
2.3 Fourier Transforms. 26
2.3.1 Fourier Integral . 27
Theorems. 28
Some Transform Pairs. 29
Discrete Fourier Transform. 31
2.3.2 Summary. 32
2.4 Digital Filtering. 35
2.4.1 Moving Average Filter. 35
2.4.2 Ideal Lowpass Filter. 37
2.5 To Probe Further. 38
Digital Image Processing 41
3.1 Image Models. 42
3.2 Image Characteristics. 44
3.2.1 Average and Standard Deviation. 44
3.2.2 Entropy. 45
3.2.3 Histogram. 45
3.2.4 Moments. 46
3.3 Image Enhancement and Restoration. 47
3.3.1 Histogram Modifications. 49
Contrast Stretching. 49
Histogram Equalization . 50
3.3.2 Smoothing Operators. 51
Averaging Operator. 52
Gaussian Filter. 53
3.3.3 Sharpening Operators . 54
3.3.4 Difference Operators. 54
Image Gradient. 54
Gradient Image Representation. 57
Laplace Operator . 57
3.3.5 Image Correction . 59
Median Filter. 60
Eliminating Erroneous Pixels. 60
Eliminating Erroneous Rows or Columns. 61
3.4 Geometric Transformations. 62
3.4.1 Size of Transformed Image. 63
3.4.2 Resampling. 64
3.5 Image Segmentation. 66
3.5.1 Histogram Thresholding. 67
3.5.2 Co-Occurrence Matrix. 69
3.5.3 Texture Segmentation by Gabor Filters. 72
Gabor Functions. 73
CONTENTS
Selection of Filter Parameters. 73
3.6 To Probe Further. 75
Human Vision 77
4.1 Overview of Human Visual System. 77
4.2 The Eye. 80
4.2.1 The Eyeball. 80
4.2.2 Optical Properties of the Eye. 81
Image Formation. 81
Resolution. 82
4.2.3 Photometric Properties of the Photoreceptors. 85
Response of Ganglion Cells: Receptive Fields. 87
4.3 Visual Cortex. 89
4.3.1 Overview. 89
4.3.2 Cortical Receptive Fields. 91
Orientation Sensitive Cells. 91
Direction Sensitive Cells. 91
End-Stopped Cells. 91
Binocular Sensitive Cells. 92
4.4 Visual Perception . 92
4.4.1 Perceptual Organization. 94
4.4.2 Other Perceptual Processes. 95
4.5 Marr's Theory about Vision. 97
4.5.1 Primal Sketch. 97
4.5.2 2.5-D Sketch . 98
4.5.3 3-D Model Representation. 99
4.6 To Probe Further. 10°
Computer Vision 101
5.1 Background. 10^
5.2 Key Concepts, Key Issues. 105
5.2.1 Vision is Modular and Hierarchical . 105
5.2.2 Vision is Ill-Posed. 106
5.2.3 Transition from Early Vision to Late Vision. 107
5.3 Edge Detection. 108
5.3.1 Detecting Edge Pixels. 110
Laplacian of Gaussian (LoG) Edge Operator. HI
5.3.2 Linking Edge Pixels. 114
5.4 Scale-Space Theory and Image Pyramids. 116
5.4.1 Scale-Space Generation. 116
lift
5.4.2 Image Pyramids. Ll°
5.5 Perceptual Organization.
xiv CONTENTS
5.5.1 Background. 12°
5.5.2 Analysis of Blockworld Scenes. I21
5.5.3 Curvilinear Segmentation. 121
Hough Transform. 121
Virtual Lines.
5.5.4 Region Segmentation.
5.5.5 More General Approaches. 124
5.6 Object Recognition . 125
5.6.1 Global Model-Based Recognition. 126
Matching Geometric Structures. 126
Matching (/ - s Curves. 126
Matching Moment Invariants. 127
5.6.2 Feature Matching With Geometric Constraints . 128
Correspondence Problem. 129
Verifying Hypotheses. 131
5.6.3 Nonmodel-Based Object Recognition. 132
5.7 To Probe Further. 132
Radiometry and Photometry 135
6.1 Electromagnetic Radiation. 135
6.1.1 Wave Characteristic of EMR. 136
6.1.2 Quantum Nature of Radiation. 136
6.1.3 Electromagnetic Spectrum. 137
6.2 Radiometry. 139
6.2.1 Solid Angle. 139
6.2.2 Radiometrie Quantities. 140
Radiant Energy, Q. 140
Radiant Flux, $. 140
Radiant Flux Density, E and M . 141
Radiant Intensity, I. 141
Radiance, L. 142
6.2.3 Lambertian Radiators. 143
6.2.4 Relationship of Radiometrie Quantities. 143
Relationship Between Radiance and Irradiance. 143
Relationship Between Radiance and Flux. 144
6.2.5 Thermal Radiation. 145
6.2.6 Photon Flux. 147
6.3 Photometry. 148
6.3.1 Photometric Quantities. 148
Luminous Energy, Q . 148
Luminous Flux, i . 148
Luminous Flux Densities, E and M. 148
CONTENTS xv
Luminous Intensity, /. 149
Luminance, L. 149
6.3.2 Relationship Between Radiant and Photometric Quan-
tities . 149
6.4 Radiative Energy Transfer. 149
6.4.1 General Case. 150
6.4.2 Radiative Energy Transfer Through Lens System . 151
Flux Across Aperture. 151
Irradiance at Image Plane . 152
6.5 To Probe Further. 154
II Fundamentals of Digital Photogrammetry 155
7 Electronic Imaging Systems 157
7.1 Introduction. 158
7.2 CCD Sensors: Working Principle and Properties. 160
7.2.1 Working Principle. 160
Linear Array With Bilinear Readout. 163
Frame Transfer. 163
Interline Transfer. 163
Time-Delay and Integration (TDI) Transfer. 164
7.2.2 Major Properties. 165
Noise. 165
Spectral Response. 165
Linearity and Dynamic Range. 167
7.3 Solid-State Cameras. i68
7.3.1 Camera Overview. 169
7.3.2 Analog Output. 171
7.3.3 Line Cameras. 172
7.3.4 Comparison Between Analog and Digital Cameras . 177
7.4 Frame Grabbers . 182
7.4.1 Timing Circuitry. 183
7.4.2 A/D Converter. 183
8 Scanners 189
8.1 Introduction. 189
8.2 Drum Scanners vs. Flatbed Scanners . 190
8.3 Principal Components of Flatbed Scanners. 191
8.3.1 Illumination and Optic System. 191
8.3.2 Photo Carrier. 19^
8.3.3 Sensor.
8.3.4 Scanner Electronics.
xvj CONTENTS
8.3.5 Host Computer. 196
8.4 Pixel Size. 197
8.4.1 Relationship Between Sensor Pixel and Scanner Pixel . 197
8.4.2 Relationship Between Scanner Pixel and Photo Pixel . . 198
8.5 Potential Error Sources. 199
8.5.1 Geometry: Position and Resolution. 199
8.5.2 Radiometrie Representation. 200
9 Digital Photogrammetric Workstations 203
9.1 Background. 203
9.1.1 Digital Photogrammetric Workstation and Digital Pho-
togrammetry Environment. 204
9.1.2 Historical Perspective. 205
9.1.3 Current Status. 207
9.1.4 Classification of Digital Photogrammetric Workstations 208
9.2 Basic System Components. 209
9.3 Basic System Functionality. 211
9.3.1 Storage System. 211
9.3.2 Viewing and Measuring System. 213
9.3.3 Stereoscopic Viewing. 215
9.3.4 Roaming. 218
9.4 Application Functionality . 220
9.4.1 Preparation. 221
9.4.2 Orientation Procedures. 222
Interior Orientation. 222
Relative Orientation. 222
Absolute Orientation. 223
9.4.3 Digital Aerial Triangulation. 224
9.4.4 Automatic DEM Generation. 224
9.4.5 Digital Orthophoto Production. 225
9.5 .Analytical Plotters vs. DPWs. 225
9.6 Summary. 227
10 Image Matching Fundamentals 231
10.1 Introduction. 231
10.1.1 Historical Remarks. 231
10.1.2 Terminology, Working Definitions. 232
10.1.3 Problem Statement. 234
10.2 Fundamental Problems of Image Matching. 234
10.2.1 Search Space, Uniqueness of Matching Entity. 234
10.2.2 Approximations, Constraints and Assumptions . 235
10.2.3 Geometric Distortions of Matching Entities. 237
CONTENTS xvjj
Geometric Distortion Due to Orientation Parameters . 238
Effect of Tilted Surface on Geometric Distortions . . . 239
Effect of Relief on Geometric Distortions. 241
10.3 Solutions to the Fundamental Problems . 242
10.3.1 Search Space and Approximations. 242
Epipolar Lines . 242
Vertical line Locus. 246
Hierarchical Approach. 249
10.3.2 Uniqueness of Matching Entity. 251
10.4 Area-Based Matching. 252
10.4.1 Correlation. 254
Cross-Correlation Factor. 254
Maximum Correlation Factor. 255
Procedure. 257
10.4.2 Least-Squares Matching . 257
Mathematical Model. 258
Adjustment Procedure. 262
11 Advanced Image Matching Methods 267
11.1 Feature-Based Matching . 268
11.1.1 Feature Extraction. 268
Interest Points. 268
Edge Detection. 269
Extracting Regions. 269
11.1.2 Matching Interest Points. 270
11.1.3 Matching Edge Pixels. 271
11.1.4Matching Entire Edges . 274
tfj - s Approach. 2 74
Generalized Hough Transform. 277
11.2 Relational Matching. 279
11.2.1 Description of Primitives and Relations . 281
11.2.2 Evaluation Function. 283
11.2.3 Tree Search. 284
11.3 Template Matching. 286
11.3.1 Matching Environment. 287
11.3.2 Matching Strategy. 287
11.3.3 Target Detection. 288
Computational Approach. 288
Histogram Thresholding. 289
Cross-Correlation. 290
Feature-Based Matching. 290
11.3.4 Precise Localization. 291
CONTENTS
Area-Based Methods . 291
Feature-Based Methods. 295
12 Computing Normalized Images 301
12.1 Introduction. 302
12.2 Epipolar Geometry. 304
12.3 Transformation from Original to Normalized Image. 305
12.3.1 Transformation Using Collinearity Equations. 308
12.3.2 Projective Transformation. 308
12.4 Normalized Digital Images. 309
12.4.1 Definition of Normalized Digital Image. 311
III Automatic Orientation Procedures 315
13 Automatic Interior Orientation 319
13.1 Purpose of Interior Orientation. 319
13.2 Determining Interior Orientation. 321
13.2.1 Transformation from Pixel to Image Coordinate System 321
13.2.2 Image Refinement. 322
Refraction. 323
Camera Imperfections. 324
Firm Shrinkage. 325
Scanner Errors. 325
Image Refinement Using Digital Cameras . 326
Summary of Image Refinement. 327
13.3 Interactive Interior Orientation. 327
13.4 Autonomous Interior Orientation . 329
13.4.1 Background and Motivation. 330
13.4.2 Objective of Autonomous Interior Orientation. 331
13.4.3 Assumptions. 331
13.4.4 Approaches to AIO. 333
13.4.5 The Anatomy of a Fiducial Mark. 334
13.5 Area-Based Approach. 335
13.5.1 Precise Localization. 339
13.6 Feature-Based Approach. 342
13.6.1 Detecting Circles. 344
13.6.2 Detecting Straight lines. 346
13.6.3 Precise Localization. 349
13.7 Summary. 351
CONTENTS xjx
14 Automatic Relative Orientation 355
14.1 Background. 355
14.1.1 Traditional vs. Automatic Orientation. 356
14.1.2 Mathematical Models for Relative Orientation. 357
Collinearity Model. 358
Coplanarity Model. 360
Linear Models. 362
14.2 Interactive Relative Orientation. 362
14.3 Automatic Orientation with Interest Points . 363
14.3.1 Extracting Interest Points. 363
14.3.2 Matching Interest Points. 364
14.4 Automatic Orientation with Edge Pixels. 367
14.4.1 Matching Edges . 367
14.4.2 Computing Orientation Parameters with Characteristic
Edge Points. 367
14.5 Automatic Orientation with Edge Entities. 368
14.5.1 Relevant Edge Characteristics. 370
Edge Pixels Are Not Necessarily Conjugate. 370
Ends of Edges are Ill-Defined. 371
Accuracy of Edge Pixels . 371
14.5.2 Computation of the Orientation Parameters. 372
14.5.3 Computation of the Surface. 375
14.5.4 Strategy. 377
14.6 Computing Orientation Parameters Without Prior Matching . 377
14.6.1 Principle. 377
14.6.2 Matching Edges by Trial and Error. 380
14.7 Summary. 382
15 Automatic Exterior Orientation 387
15.1 Direct vs. Indirect Orientation . 389
15.2 Background. 392
15.2.1 Single Image Resection. 392
15.2.2 Absolute Orientation. 393
15.2.3 Exterior Orientation Parameters from Relative and Ab-
solute Orientation. 39j
15.3 Automatic Orientation with Control Points. 395
15.3.1 Automatic Detection of Targets. 396
15.3.2 Automatic Detection of Topographic Control Points . . 398
15.4 Automatic Orientation with Control Features. 399
15.4.1 Matching Extracted Features with Control Features . 400
15.4.2 Computing Orientation Parameters with Control Lines 403
15.5 Automatic Orientation with Control Surfaces. 407
xx CONTENTS
15.5.1 Problem Statement. 407
15.5.2 Solution. 408
Geometric Considerations. 408
Mathematical Model. 409
15.5.3 Procedure. 411
15.6 Summary. 412
Author Index 417
Subject Index 421 |
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| illustrated | Illustrated |
| index_date | 2024-07-02T18:40:02Z |
| indexdate | 2024-07-09T21:06:54Z |
| institution | BVB |
| isbn | 0967765307 0967765315 |
| language | English |
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| spelling | Schenk, Toni Verfasser aut Digital photogrammetry Volume 1 Background, fundamentals automatic orientation procedures Toni Schenk Laurelville, OH TerraScience 1999 422 S. Ill., graf. Darst. txt rdacontent n rdamedia nc rdacarrier (DE-604)BV022821061 1 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016026463&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Schenk, Toni Digital photogrammetry |
| title | Digital photogrammetry |
| title_auth | Digital photogrammetry |
| title_exact_search | Digital photogrammetry |
| title_exact_search_txtP | Digital photogrammetry |
| title_full | Digital photogrammetry Volume 1 Background, fundamentals automatic orientation procedures Toni Schenk |
| title_fullStr | Digital photogrammetry Volume 1 Background, fundamentals automatic orientation procedures Toni Schenk |
| title_full_unstemmed | Digital photogrammetry Volume 1 Background, fundamentals automatic orientation procedures Toni Schenk |
| title_short | Digital photogrammetry |
| title_sort | digital photogrammetry background fundamentals automatic orientation procedures |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016026463&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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