Computer imaging: digital image analysis and processing
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boca Raton [u.a.]
Taylor & Francis
2005
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| Schlagworte: | |
| Online-Zugang: | Publisher description Inhaltsverzeichnis |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | 659 S. Ill., graph. Darst. 1 CD-ROM (12 cm) |
| ISBN: | 0849329191 |
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| 245 | 1 | 0 | |a Computer imaging |b digital image analysis and processing |c Scott E. Umbaugh |
| 264 | 1 | |a Boca Raton [u.a.] |b Taylor & Francis |c 2005 | |
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| 650 | 4 | |a Image processing |x Digital techniques | |
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Datensatz im Suchindex
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| adam_text | COMPUTER IMAGING DIGITAL IMAGE ANALYSIS AND PROCESSING SCOTT E UMBAUGH
SOUTHERN ILLINOIS UNIVERSITY EDWARDSVILLE TAYLOR &. FRANCIS TAYLOR &.
FRANCIS GROUP BOCA RATON LONDON NEW YORK SINGAPORE A CRC TITLE, PART OF
THE TAYLOR & FRANCIS IMPRINT, A MEMBER OF THE TAYLOR & FRANCIS GROUP,
THE ACADEMIC DIVISION OF T&F INFORMA PIC. CONTENTS SECTION I
INTRODUCTION TO COMPUTER IMAGING CHAPTER 1 COMPUTER IMAGING 1.1 OVERVIEW
3 1.2 IMAGE ANALYSIS AND COMPUTER VISION 5 1.3 IMAGE PROCESSING 8 1.4
KEY POINTS 11 1.5 REFERENCES AND FURTHER READING 13 1.6 EXERCISES 14
CHAPTER 2 COMPUTER IMAGING SYSTEMS 2.1 IMAGING SYSTEMS OVERVIEW 15 2.2
IMAGE FORMATION AND SENSING 18 2.2.1 VISIBLE LIGHT IMAGING 20 2.2.2
IMAGING OUTSIDE THE VISIBLE RANGE OF THE EM SPECTRUM 26 2.2.3 ACOUSTIC
IMAGING 29 2.2.4 ELECTRON IMAGING 30 2.2.5 LASER IMAGING 31 2.2.6
COMPUTER GENERATED IMAGES 32 2.3 THE CVIPTOOLS SOFTWARE 32 2.3.1 MAIN
WINDOW 34 2.3.2 IMAGE VIEWER. 36 2.3.3 ANALYSIS WINDOW 37 2.3.4
ENHANCEMENT WINDOW 37 2.3.5 RESTORATION WINDOW 39 2.3.6 COMPRESSION
WINDOW 39 2.3.7 UTILITIES WINDOW 41 2.3.8 HELP WINDOW 41 2.4 IMAGE
REPRESENTATION 43 2.4.1 BINARY IMAGES 45 2.4.2 GRAY-SCALE IMAGES 45
2.4.3 COLOR IMAGES 45 2.4.4 MULTISPECTRAL IMAGES 54 2.4.5 DIGITAL IMAGE
FILE FORMATS 54 2.5 KEY POINTS 57 2.6 REFERENCES AND FURTHER READING 60
2.7 EXERCISES 62 2.7.1 PROGRAMMING EXERCISE: INTRODUCTION TO CVIPLAB 63
SECTION II DIGITAL IMAGE ANALYSIS CHAPTER 3 INTRODUCTION TO DIGITAL
IMAGE ANALYSIS 3.1 INTRODUCTION 67 3.1.1 OVERVIEW 67 3.1.2 SYSTEM MODEL
68 3.2 PREPROCESSING 69 3.2.1 REGION OF INTEREST IMAGE GEOMETRY 69 3.2.2
ARITHMETIC AND LOGIC OPERATIONS 75 3.2.3 SPATIAL FILTERS 81 3.2.4 IMAGE
QUANTIZATION 86 3.3 BINARY IMAGE ANALYSIS 93 3.3.1 THRESHOLDING VIA
HISTOGRAM 93 3.3.2 CONNECTIVITY AND LABELING 94 3.3.3 BASIC BINARY
OBJECT FEATURES 98 3.3.4 BINARY OBJECT CLASSIFICATION 100 3.4 KEY POINTS
109 3.5 REFERENCES AND FURTHER READING 113 3.6 EXERCISES 114 3.6.1
PROGRAMMING EXERCISE: IMAGE GEOMETRY 116 3.6.2 PROGRAMMING EXERCISE:
ARITHMETIC/LOGIC OPERATIONS 117 3.6.3 PROGRAMMING EXERCISE: SPATIAL
FILTERS 117 3.6.4 PROGRAMMING EXERCISE: IMAGE QUANTIZATION 118 3.6.5
PROGRAMMING EXERCISE: CONNECTIVITY AND LABELING 118 3.6.6 PROGRAMMING
EXERCISE: BINARY OBJECT FEATURES 119 CHAPTER 4 SEGMENTATION AND
EDGE/LINE DETECTION 4.1 INTRODUCTION AND OVERVIEW 121 4.2 EDGE/LINE
DETECTION 122 4.2.1 GRADIENT OPERATORS 124 4.2.2 COMPASS MASKS 129 4.2.3
ADVANCED EDGE DETECTORS 130 4.2.4 EDGES IN COLOR IMAGES 134 4.2.5 EDGE
DETECTOR PERFORMANCE 135 4.2.6 HOUGH TRANSFORM 143 4.2.6.1 CVIPTOOLS
PARAMETERS FOR THE HOUGH TRANSFORM 151 4.3 SEGMENTATION 151 4.3.1 REGION
GROWING AND SHRINKING 151 4.3.2 CLUSTERING TECHNIQUES 157 4.3.3 BOUNDARY
DETECTION 163 4.3.4 COMBINED SEGMENTATION APPROACHES 168 4.3.5
MORPHOLOGICAL FILTERING 168 4.4 KEY POINTS 183 4.5 REFERENCES AND
FURTHER READING 192 4.6 EXERCISES 193 4.6.1 PROGRAMMING EXERCISE: EDGE
DETECTION*ROBERTS AND SOBEL 198 4.6.2 PROGRAMMING EXERCISE: HOUGH
TRANSFORM 199 4.6.3 PROGRAMMING EXERCISE: SCT/CENTER SEGMENTATION 199
4.6.4 PROGRAMMING EXERCISE: HISTOGRAM THRESHOLDING SEGMENTATION 199
4.6.5 PROGRAMMING EXERCISE: MORPHOLOGICAL FILTERS 199 4.6.6 PROGRAMMING
EXERCISE: ITERATIVE MORPHOLOGICAL FILTERS 199 CHAPTER 5 DISCRETE
TRANSFORMS 5.1 INTRODUCTION AND OVERVIEW 201 5.2 FOURIER TRANSFORM 206
5.2.1 THE ONE-DIMENSIONAL DISCRETE FOURIER TRANSFORM 209 5.2.2 THE
TWO-DIMENSIONAL DISCRETE FOURIER TRANSFORM 212 5.2.3 FOURIER TRANSFORM
PROPERTIES 214 5.2.3.1 LINEARITY 215 5.2.3.2 CONVOLUTION 215 5.2.3.3
TRANSLATION 215 5.2.3.4 MODULATION 215 5.2.3.5 ROTATION 216 5.2.3.6
PERIODICITY 217 5.2.4 DISPLAYING THE FOURIER SPECTRUM 218 5.3 COSINE
TRANSFORM 220 5.4 WALSH-HADAMARD TRANSFORM 224 5.5 HAAR TRANSFORM 228
5.6 PRINCIPAL COMPONENTS TRANSFORM 229 5.7 FILTERING 231 5.7.1 LOWPASS
FILTERS 232 5.7.2 HIGHPASS FILTERS 234 5.7.3 BANDPASS AND BANDREJECT
FILTERS 238 5.8 WAVELET TRANSFORM 239 5.9 KEY POINTS 245 5.10 REFERENCES
AND FURTHER READING 252 5.11 EXERCISES 253 5.11.1 PROGRAMMING EXERCISE:
FILTERING 260 5.11.2 PROGRAMMING EXERCISE: FOURIER TRANSFORM 260 5.11.3
PROGRAMMING EXERCISE: DISCRETE COSINE TRANSFORM 260 5.11.4 PROGRAMMING
EXERCISE: WALSH-HADAMARD TRANSFORM 260 5.11.5 PROGRAMMING EXERCISE: HAAR
TRANSFORM 260 5.11.6 PROGRAMMING EXERCISE: WAVELET TRANSFORM 260 5.11.7
PROGRAMMING EXERCISE: CVIPTOOLS LIBRARY FILTER FUNCTIONS 260 CHAPTER 6
FEATURE ANALYSIS AND PATTERN CLASSIFICATION 6.1 INTRODUCTION AND
OVERVIEW 261 6.2 FEATURE EXTRACTION 262 6.2.1 SHAPE FEATURES 262 6.2.2
HISTOGRAM FEATURES 265 6.2.3 COLOR FEATURES 269 6.2.4 SPECTRAL FEATURES
271 6.2.5 TEXTURE FEATURES 273 6.2.6 FEATURE EXTRACTION WITH CVIPTOOLS
277 6.3 FEATURE ANALYSIS 278 6.3.1 FEATURE VECTORS AND FEATURE SPACES
280 6.3.2 DISTANCE AND SIMILARITY MEASURES 281 6.3.3 DATA PREPROCESSING
282 6.4 PATTERN CLASSIFICATION 285 6.4.1 ALGORITHM DEVELOPMENT: TRAINING
AND TESTING METHODS 286 6.4.2 CLASSIFICATION ALGORITHMS AND METHODS 288
6.5 KEY POINTS 291 6.6 REFERENCES AND FURTHER READING 299 6.7 EXERCISES
300 6.7.1 PROGRAMMING EXERCISE: PERIMETER 305 6.7.2 PROGRAMMING
EXERCISE: THINNESS RATIO 305 6.7.3 PROGRAMMING EXERCISE: ASPECT RATIO
306 6.7.4 PROGRAMMING EXERCISE: MOMENT-BASED RST-INVARIANT FEATURES 306
6.7.5 PROGRAMMING EXERCISE: HISTOGRAM FEATURES 306 6.7.6 PROGRAMMING
EXERCISE: COLOR FEATURES 306 6.7.7 PROGRAMMING EXERCISE: SPECTRAL
FEATURES 306 6.7.8 PROGRAMMING EXERCISE: TEXTURE FEATURES 307 6.7.9
PROGRAMMING EXERCISE: DISTANCE AND SIMILARITY MEASURES 307 6.7.10
PROGRAMMING EXERCISE: TEMPLATE MATCHING 308 6.7.11 PROGRAMMING EXERCISE:
PATTERN CLASSIFICATION 1 308 6.7.12 PROGRAMMING EXERCISE: PATTERN
CLASSIFICATION II 309 SECTION III DIGITAL IMAGE PROCESSING CHAPTER 7
DIGITAL IMAGE PROCESSING AND VISUAL PERCEPTION 7.1 INTRODUCTION AND
OVERVIEW 313 7.2 HUMAN VISUAL PERCEPTION 313 7.2.1 THE HUMAN VISUAL
SYSTEM 314 7.2.2 SPATIAL FREQUENCY RESOLUTION 320 7.2.3 BRIGHTNESS
ADAPTATION 323 7.2.4 TEMPORAL RESOLUTION 324 7.2.5 PERCEPTION AND
ILLUSION 326 7.3 IMAGE FIDELITY CRITERIA 327 7.3.1 OBJECTIVE FIDELITY
MEASURES 328 7.3.2 SUBJECTIVE FIDELITY MEASURES 331 7.4 KEY POINTS 332
7.5 REFERENCES AND FURTHER READING 336 7.6 EXERCISES 337 7.6.1
PROGRAMMING EXERCISE: SPATIAL RESOLUTION 339 7.6.2 PROGRAMMING EXERCISE:
BRIGHTNESS ADAPTATION 339 7.6.3 PROGRAMMING EXERCISE: OPTICAL ILLUSIONS
340 CHAPTER 8 IMAGE ENHANCEMENT 8.1 INTRODUCTION AND OVERVIEW 341 8.2
GRAY SCALE MODIFICATION 343 8.2.1 MAPPING EQUATIONS 343 8.2.2 HISTOGRAM
MODIFICATION 353 8.2.3 ADAPTIVE CONTRAST ENHANCEMENT 364 8.2.4 COLOR 371
8.3 IMAGE SHARPENING 377 8.3.1 HIGHPASS FILTERING 377 8.3.2 HIGH
FREQUENCY EMPHASIS 378 8.3.3 DIRECTIONAL DIFFERENCE FILTERS 379 8.3.4
HOMOMORPHIC FILTERING 381 8.3.5 UNSHARP MASKING 383 8.3.6 EDGE
DETECTOR-BASED SHARPENING ALGORITHMS 384 8.4 IMAGE SMOOTHING 387 8.4.1
FREQUENCY DOMAIN LOWPASS FILTERING 387 8.4.2 CONVOLUTION MASK LOWPASS
FILTERING 387 8.4.3 MEDIAN FILTERING 388 8.5 KEY POINTS 391 8.6
REFERENCES AND FURTHER READING 397 8.7 EXERCISES 398 8.7.1 PROGRAMMING
EXERCISE: DIGITAL NEGATIVE 403 8.7.2 PROGRAMMING EXERCISE: PIECEWISE
GRAY LEVEL MAPPING 404 8.7.3 PROGRAMMING EXERCISE: GAMMA CORRECTION 404
8.7.4 PROGRAMMING EXERCISE: HISTOGRAM MODIFICATION 404 8.7.5 PROGRAMMING
EXERCISE: HISTOGRAM EQUALIZATION 404 8.7.6 PROGRAMMING EXERCISE: ACE
FILTERS 405 8.7.7 PROGRAMMING EXERCISE: PSEUDOCOLOR 405 8.7.8
PROGRAMMING EXERCISE: BASIC ENHANCEMENT CONVOLUTION MASKS 405 8.7.9
PROGRAMMING EXERCISE: UNSHARP MASKING 406 8.7.10 PROGRAMMING EXERCISE:
SHARPENING ALGORITHMS 406 8.7.11 PROGRAMMING EXERCISE: MEDIAN FILTERING
406 CHAPTER 9 IMAGE RESTORATION 9.1 INTRODUCTION AND OVERVIEW 407 9.1.1
SYSTEM MODEL 407 9.2 NOISE MODELS 409 9.2.1 NOISE HISTOGRAMS 409 9.2.2
PERIODIC NOISE 412 9.2.3 ESTIMATION OF NOISE 414 9.3 NOISE REMOVAL USING
SPATIAL FILTERS 415 9.3.1 ORDER FILTERS 417 9.3.2 MEAN FILTERS 421 9.3.3
ADAPTIVE FILTERS 426 9.4 THE DEGRADATION FUNCTION 431 9.4.1 THE SPATIAL
DOMAIN*THE POINT SPREAD FUNCTION 431 9.4.2 THE FREQUENCY DOMAIN*THE
MODULATION/OPTICAL TRANSFER FUNCTION 435 9.4.3 ESTIMATION OF THE
DEGRADATION FUNCTION 436 9.5 FREQUENCY DOMAIN FILTERS 436 9.5.1 INVERSE
FILTER 438 9.5.2 WIENER FILTER 441 9.5.3 CONSTRAINED LEAST SQUARES
FILTER 442 9.5.4 GEOMETRIC MEAN FILTERS 444 9.5.5 ADAPTIVE FILTERING 446
9.5.6 BANDPASS, BANDREJECT AND NOTCH FILTERS 447 9.5.7 PRACTICAL
CONSIDERATIONS 449 9.6 GEOMETRIC TRANSFORMS 451 9.6.1 SPATIAL TRANSFORMS
452 9.6.2 GRAY LEVEL INTERPOLATION 455 9.6.3 THE GEOMETRIC RESTORATION
PROCEDURE 457 9.6.4 GEOMETRIC RESTORATION WITH CVIPTOOLS 458 9.7 KEY
POINTS 460 9.8 REFERENCES AND FURTHER READING 471 9.9 EXERCISES 473
9.9.1 PROGRAMMING EXERCISE: NOISE 478 9.9.2 PROGRAMMING EXERCISE: ORDER
FILTERS 479 9.9.3 PROGRAMMING EXERCISE: MEAN FILTERS 479 9.9.4
PROGRAMMING EXERCISE: MMSE FILTER 479 9.9.5 PROGRAMMING EXERCISE:
FREQUENCY DOMAIN FILTERS 479 9.9.6 PROGRAMMING EXERCISE: GEOMETRIC
TRANSFORMS 480 CHAPTER 10 IMAGE COMPRESSION 10.1 INTRODUCTION AND
OVERVIEW 481 10.1.1 COMPRESSION SYSTEM MODEL 485 10.2 LOSSLESS
COMPRESSION METHODS 489 10.2.1 HUFFMAN CODING 492 10.2.2 RUN-LENGTH
CODING 495 10.2.3 LEMPEL-ZIV-WELCH CODING 498 10.2.4 ARITHMETIC CODING
499 10.3 LOSSY COMPRESSION METHODS 500 10.3.1 GRAY-LEVEL RUN-LENGTH
CODING 501 10.3.2 BLOCK TRUNCATION CODING 504 10.3.3 VECTOR QUANTIZATION
509 10.3.4 DIFFERENTIAL PREDICTIVE CODING 513 10.3.5 MODEL-BASED AND
FRACTAL COMPRESSION 519 10.3.6 TRANSFORM CODING 521 10.3.7 HYBRID AND
WAVELET METHODS 527 10.4 KEY POINTS 534 10.5 REFERENCES AND FURTHER
READING 540 10.6 EXERCISES 541 10.6.1 PROGRAMMING EXERCISE:
SIGNAL-TO-NOISE RATIO AND ROOT-MEAN-SQUARE ERROR METRICS 546 10.6.2
PROGRAMMING EXERCISE: HUFFMAN CODING 546 10.6.3 PROGRAMMING EXERCISE:
RUN-LENGTH CODING 546 10.6.4 PROGRAMMING EXERCISE: BLOCK TRUNCATION
CODING 546 10.6.5 PROGRAMMING EXERCISE: DIFFERENTIAL PREDICTIVE CODING
546 10.6.6 PROGRAMMING EXERCISE: ZONAL CODING 547 SECTION IV PROGRAMMING
WITH CVIPTOOLS CHAPTER 11 CVIPLAB 11.1 INTRODUCTION TO CVIPLAB 551 11.2
TOOLKITS, TOOLBOXES AND APPLICATION LIBRARIES 556 11.3 COMPILING AND
LINKING CVIPLAB 557 11.3.1 HOW TO BUILD THE CVIPLAB PROJECT WITH
MICROSOFT S VISUAL C++ 6.0 557 11.3.2 THE MECHANICS OF ADDING A FUNCTION
WITH MICROSOFT S VISUAL C++ 6.0 559 11.3.3 USING CVIPLAB IN THE
PROGRAMMING EXERCISES 562 11.4 IMAGE DATA AND FILE STRUCTURES 566 11.5
CVIP PROJECTS 573 11.5.1 COMPUTER VISION PROJECTS 573 11.5.2 DIGITAL
IMAGE PROCESSING PROJECTS 574 CHAPTER 12 CVIPTOOLS C FUNCTION LIBRARIES
12.1 INTRODUCTION AND OVERVIEW 577 12.2 ARITHMETIC AND LOGIC
LIBRARY*ARITHLOGIC.LIB 577 12.3 BAND IMAGE LIBRARY*BAND.LIB 578 12.4
COLOR IMAGE LIBRARY*COLOR.LIB 578 12.5 COMPRESSION
LIBRARY*COMPRESSION.LIB 579 12.6 CONVERSION LIBRARY*CON VERSION, LIB 583
12.7 DISPLAY LIBRARY*DISPLAY.LIB 585 12.8 FEATURE EXTRACTION
LIBRARY*FEATURE.LIB 585 12.9 GEOMETRY LIBRARY*GEOMETRY.LIB 588 12.10
HISTOGRAM LIBRARY*HISTOGRAM.LIB 592 12.11 IMAGE LIBRARY*IMAGE.LIB 593
12.12 DATA MAPPING LIBRARY*MAPPING.LIB 594 12.13 MORPHOLOGICAL
LIBRARY*MORPHOLOGICAL.LIB 595 12.14 NOISE LIBRARY*NOISE.LIB 597 12.15
SEGMENTATION LIBRARY*SEGMENTATION.LIB 597 12.16 SPATIAL FILTER
LIBRARY*SPATIALFILTER.LIB 599 12.17 TRANSFORM LIBRARY*TRANSFORM.LIB 603
12.18 TRANSFORM FILTER LIBRARY*TRANSFORMFILTER.LIB 604 SECTION V
APPENDICES A. THE CVIPTOOLS CD-ROM 611 B. INSTALLING AND UPDATING
CVIPTOOLS 613 C. CVIPTOOLS C FUNCTIONS 617 D. CVIP RESOURCES 629 E.
CVIPTOOLS SOFTWARE ORGANIZATION 633 F. COMMON OBJECT MODULE (COM)
FUNCTIONS* CVIPTOOLS.DLL 635 INDEX 645
|
| adam_txt |
COMPUTER IMAGING DIGITAL IMAGE ANALYSIS AND PROCESSING SCOTT E UMBAUGH
SOUTHERN ILLINOIS UNIVERSITY EDWARDSVILLE TAYLOR &. FRANCIS TAYLOR &.
FRANCIS GROUP BOCA RATON LONDON NEW YORK SINGAPORE A CRC TITLE, PART OF
THE TAYLOR & FRANCIS IMPRINT, A MEMBER OF THE TAYLOR & FRANCIS GROUP,
THE ACADEMIC DIVISION OF T&F INFORMA PIC. CONTENTS SECTION I
INTRODUCTION TO COMPUTER IMAGING CHAPTER 1 COMPUTER IMAGING 1.1 OVERVIEW
3 1.2 IMAGE ANALYSIS AND COMPUTER VISION 5 1.3 IMAGE PROCESSING 8 1.4
KEY POINTS 11 1.5 REFERENCES AND FURTHER READING 13 1.6 EXERCISES 14
CHAPTER 2 COMPUTER IMAGING SYSTEMS 2.1 IMAGING SYSTEMS OVERVIEW 15 2.2
IMAGE FORMATION AND SENSING 18 2.2.1 VISIBLE LIGHT IMAGING 20 2.2.2
IMAGING OUTSIDE THE VISIBLE RANGE OF THE EM SPECTRUM 26 2.2.3 ACOUSTIC
IMAGING 29 2.2.4 ELECTRON IMAGING 30 2.2.5 LASER IMAGING 31 2.2.6
COMPUTER GENERATED IMAGES 32 2.3 THE CVIPTOOLS SOFTWARE 32 2.3.1 MAIN
WINDOW 34 2.3.2 IMAGE VIEWER. 36 2.3.3 ANALYSIS WINDOW 37 2.3.4
ENHANCEMENT WINDOW 37 2.3.5 RESTORATION WINDOW 39 2.3.6 COMPRESSION
WINDOW 39 2.3.7 UTILITIES WINDOW 41 2.3.8 HELP WINDOW 41 2.4 IMAGE
REPRESENTATION 43 2.4.1 BINARY IMAGES 45 2.4.2 GRAY-SCALE IMAGES 45
2.4.3 COLOR IMAGES 45 2.4.4 MULTISPECTRAL IMAGES 54 2.4.5 DIGITAL IMAGE
FILE FORMATS 54 2.5 KEY POINTS 57 2.6 REFERENCES AND FURTHER READING 60
2.7 EXERCISES 62 2.7.1 PROGRAMMING EXERCISE: INTRODUCTION TO CVIPLAB 63
SECTION II DIGITAL IMAGE ANALYSIS CHAPTER 3 INTRODUCTION TO DIGITAL
IMAGE ANALYSIS 3.1 INTRODUCTION 67 3.1.1 OVERVIEW 67 3.1.2 SYSTEM MODEL
68 3.2 PREPROCESSING 69 3.2.1 REGION OF INTEREST IMAGE GEOMETRY 69 3.2.2
ARITHMETIC AND LOGIC OPERATIONS 75 3.2.3 SPATIAL FILTERS 81 3.2.4 IMAGE
QUANTIZATION 86 3.3 BINARY IMAGE ANALYSIS 93 3.3.1 THRESHOLDING VIA
HISTOGRAM 93 3.3.2 CONNECTIVITY AND LABELING 94 3.3.3 BASIC BINARY
OBJECT FEATURES 98 3.3.4 BINARY OBJECT CLASSIFICATION 100 3.4 KEY POINTS
109 3.5 REFERENCES AND FURTHER READING 113 3.6 EXERCISES 114 3.6.1
PROGRAMMING EXERCISE: IMAGE GEOMETRY 116 3.6.2 PROGRAMMING EXERCISE:
ARITHMETIC/LOGIC OPERATIONS 117 3.6.3 PROGRAMMING EXERCISE: SPATIAL
FILTERS 117 3.6.4 PROGRAMMING EXERCISE: IMAGE QUANTIZATION 118 3.6.5
PROGRAMMING EXERCISE: CONNECTIVITY AND LABELING 118 3.6.6 PROGRAMMING
EXERCISE: BINARY OBJECT FEATURES 119 CHAPTER 4 SEGMENTATION AND
EDGE/LINE DETECTION 4.1 INTRODUCTION AND OVERVIEW 121 4.2 EDGE/LINE
DETECTION 122 4.2.1 GRADIENT OPERATORS 124 4.2.2 COMPASS MASKS 129 4.2.3
ADVANCED EDGE DETECTORS 130 4.2.4 EDGES IN COLOR IMAGES 134 4.2.5 EDGE
DETECTOR PERFORMANCE 135 4.2.6 HOUGH TRANSFORM 143 4.2.6.1 CVIPTOOLS
PARAMETERS FOR THE HOUGH TRANSFORM 151 4.3 SEGMENTATION 151 4.3.1 REGION
GROWING AND SHRINKING 151 4.3.2 CLUSTERING TECHNIQUES 157 4.3.3 BOUNDARY
DETECTION 163 4.3.4 COMBINED SEGMENTATION APPROACHES 168 4.3.5
MORPHOLOGICAL FILTERING 168 4.4 KEY POINTS 183 4.5 REFERENCES AND
FURTHER READING 192 4.6 EXERCISES 193 4.6.1 PROGRAMMING EXERCISE: EDGE
DETECTION*ROBERTS AND SOBEL 198 4.6.2 PROGRAMMING EXERCISE: HOUGH
TRANSFORM 199 4.6.3 PROGRAMMING EXERCISE: SCT/CENTER SEGMENTATION 199
4.6.4 PROGRAMMING EXERCISE: HISTOGRAM THRESHOLDING SEGMENTATION 199
4.6.5 PROGRAMMING EXERCISE: MORPHOLOGICAL FILTERS 199 4.6.6 PROGRAMMING
EXERCISE: ITERATIVE MORPHOLOGICAL FILTERS 199 CHAPTER 5 DISCRETE
TRANSFORMS 5.1 INTRODUCTION AND OVERVIEW 201 5.2 FOURIER TRANSFORM 206
5.2.1 THE ONE-DIMENSIONAL DISCRETE FOURIER TRANSFORM 209 5.2.2 THE
TWO-DIMENSIONAL DISCRETE FOURIER TRANSFORM 212 5.2.3 FOURIER TRANSFORM
PROPERTIES 214 5.2.3.1 LINEARITY 215 5.2.3.2 CONVOLUTION 215 5.2.3.3
TRANSLATION 215 5.2.3.4 MODULATION 215 5.2.3.5 ROTATION 216 5.2.3.6
PERIODICITY 217 5.2.4 DISPLAYING THE FOURIER SPECTRUM 218 5.3 COSINE
TRANSFORM 220 5.4 WALSH-HADAMARD TRANSFORM 224 5.5 HAAR TRANSFORM 228
5.6 PRINCIPAL COMPONENTS TRANSFORM 229 5.7 FILTERING 231 5.7.1 LOWPASS
FILTERS 232 5.7.2 HIGHPASS FILTERS 234 5.7.3 BANDPASS AND BANDREJECT
FILTERS 238 5.8 WAVELET TRANSFORM 239 5.9 KEY POINTS 245 5.10 REFERENCES
AND FURTHER READING 252 5.11 EXERCISES 253 5.11.1 PROGRAMMING EXERCISE:
FILTERING 260 5.11.2 PROGRAMMING EXERCISE: FOURIER TRANSFORM 260 5.11.3
PROGRAMMING EXERCISE: DISCRETE COSINE TRANSFORM 260 5.11.4 PROGRAMMING
EXERCISE: WALSH-HADAMARD TRANSFORM 260 5.11.5 PROGRAMMING EXERCISE: HAAR
TRANSFORM 260 5.11.6 PROGRAMMING EXERCISE: WAVELET TRANSFORM 260 5.11.7
PROGRAMMING EXERCISE: CVIPTOOLS LIBRARY FILTER FUNCTIONS 260 CHAPTER 6
FEATURE ANALYSIS AND PATTERN CLASSIFICATION 6.1 INTRODUCTION AND
OVERVIEW 261 6.2 FEATURE EXTRACTION 262 6.2.1 SHAPE FEATURES 262 6.2.2
HISTOGRAM FEATURES 265 6.2.3 COLOR FEATURES 269 6.2.4 SPECTRAL FEATURES
271 6.2.5 TEXTURE FEATURES 273 6.2.6 FEATURE EXTRACTION WITH CVIPTOOLS
277 6.3 FEATURE ANALYSIS 278 6.3.1 FEATURE VECTORS AND FEATURE SPACES
280 6.3.2 DISTANCE AND SIMILARITY MEASURES 281 6.3.3 DATA PREPROCESSING
282 6.4 PATTERN CLASSIFICATION 285 6.4.1 ALGORITHM DEVELOPMENT: TRAINING
AND TESTING METHODS 286 6.4.2 CLASSIFICATION ALGORITHMS AND METHODS 288
6.5 KEY POINTS 291 6.6 REFERENCES AND FURTHER READING 299 6.7 EXERCISES
300 6.7.1 PROGRAMMING EXERCISE: PERIMETER 305 6.7.2 PROGRAMMING
EXERCISE: THINNESS RATIO 305 6.7.3 PROGRAMMING EXERCISE: ASPECT RATIO
306 6.7.4 PROGRAMMING EXERCISE: MOMENT-BASED RST-INVARIANT FEATURES 306
6.7.5 PROGRAMMING EXERCISE: HISTOGRAM FEATURES 306 6.7.6 PROGRAMMING
EXERCISE: COLOR FEATURES 306 6.7.7 PROGRAMMING EXERCISE: SPECTRAL
FEATURES 306 6.7.8 PROGRAMMING EXERCISE: TEXTURE FEATURES 307 6.7.9
PROGRAMMING EXERCISE: DISTANCE AND SIMILARITY MEASURES 307 6.7.10
PROGRAMMING EXERCISE: TEMPLATE MATCHING 308 6.7.11 PROGRAMMING EXERCISE:
PATTERN CLASSIFICATION 1 308 6.7.12 PROGRAMMING EXERCISE: PATTERN
CLASSIFICATION II 309 SECTION III DIGITAL IMAGE PROCESSING CHAPTER 7
DIGITAL IMAGE PROCESSING AND VISUAL PERCEPTION 7.1 INTRODUCTION AND
OVERVIEW 313 7.2 HUMAN VISUAL PERCEPTION 313 7.2.1 THE HUMAN VISUAL
SYSTEM 314 7.2.2 SPATIAL FREQUENCY RESOLUTION 320 7.2.3 BRIGHTNESS
ADAPTATION 323 7.2.4 TEMPORAL RESOLUTION 324 7.2.5 PERCEPTION AND
ILLUSION 326 7.3 IMAGE FIDELITY CRITERIA 327 7.3.1 OBJECTIVE FIDELITY
MEASURES 328 7.3.2 SUBJECTIVE FIDELITY MEASURES 331 7.4 KEY POINTS 332
7.5 REFERENCES AND FURTHER READING 336 7.6 EXERCISES 337 7.6.1
PROGRAMMING EXERCISE: SPATIAL RESOLUTION 339 7.6.2 PROGRAMMING EXERCISE:
BRIGHTNESS ADAPTATION 339 7.6.3 PROGRAMMING EXERCISE: OPTICAL ILLUSIONS
340 CHAPTER 8 IMAGE ENHANCEMENT 8.1 INTRODUCTION AND OVERVIEW 341 8.2
GRAY SCALE MODIFICATION 343 8.2.1 MAPPING EQUATIONS 343 8.2.2 HISTOGRAM
MODIFICATION 353 8.2.3 ADAPTIVE CONTRAST ENHANCEMENT 364 8.2.4 COLOR 371
8.3 IMAGE SHARPENING 377 8.3.1 HIGHPASS FILTERING 377 8.3.2 HIGH
FREQUENCY EMPHASIS 378 8.3.3 DIRECTIONAL DIFFERENCE FILTERS 379 8.3.4
HOMOMORPHIC FILTERING 381 8.3.5 UNSHARP MASKING 383 8.3.6 EDGE
DETECTOR-BASED SHARPENING ALGORITHMS 384 8.4 IMAGE SMOOTHING 387 8.4.1
FREQUENCY DOMAIN LOWPASS FILTERING 387 8.4.2 CONVOLUTION MASK LOWPASS
FILTERING 387 8.4.3 MEDIAN FILTERING 388 8.5 KEY POINTS 391 8.6
REFERENCES AND FURTHER READING 397 8.7 EXERCISES 398 8.7.1 PROGRAMMING
EXERCISE: DIGITAL NEGATIVE 403 8.7.2 PROGRAMMING EXERCISE: PIECEWISE
GRAY LEVEL MAPPING 404 8.7.3 PROGRAMMING EXERCISE: GAMMA CORRECTION 404
8.7.4 PROGRAMMING EXERCISE: HISTOGRAM MODIFICATION 404 8.7.5 PROGRAMMING
EXERCISE: HISTOGRAM EQUALIZATION 404 8.7.6 PROGRAMMING EXERCISE: ACE
FILTERS 405 8.7.7 PROGRAMMING EXERCISE: PSEUDOCOLOR 405 8.7.8
PROGRAMMING EXERCISE: BASIC ENHANCEMENT CONVOLUTION MASKS 405 8.7.9
PROGRAMMING EXERCISE: UNSHARP MASKING 406 8.7.10 PROGRAMMING EXERCISE:
SHARPENING ALGORITHMS 406 8.7.11 PROGRAMMING EXERCISE: MEDIAN FILTERING
406 CHAPTER 9 IMAGE RESTORATION 9.1 INTRODUCTION AND OVERVIEW 407 9.1.1
SYSTEM MODEL 407 9.2 NOISE MODELS 409 9.2.1 NOISE HISTOGRAMS 409 9.2.2
PERIODIC NOISE 412 9.2.3 ESTIMATION OF NOISE 414 9.3 NOISE REMOVAL USING
SPATIAL FILTERS 415 9.3.1 ORDER FILTERS 417 9.3.2 MEAN FILTERS 421 9.3.3
ADAPTIVE FILTERS 426 9.4 THE DEGRADATION FUNCTION 431 9.4.1 THE SPATIAL
DOMAIN*THE POINT SPREAD FUNCTION 431 9.4.2 THE FREQUENCY DOMAIN*THE
MODULATION/OPTICAL TRANSFER FUNCTION 435 9.4.3 ESTIMATION OF THE
DEGRADATION FUNCTION 436 9.5 FREQUENCY DOMAIN FILTERS 436 9.5.1 INVERSE
FILTER 438 9.5.2 WIENER FILTER 441 9.5.3 CONSTRAINED LEAST SQUARES
FILTER 442 9.5.4 GEOMETRIC MEAN FILTERS 444 9.5.5 ADAPTIVE FILTERING 446
9.5.6 BANDPASS, BANDREJECT AND NOTCH FILTERS 447 9.5.7 PRACTICAL
CONSIDERATIONS 449 9.6 GEOMETRIC TRANSFORMS 451 9.6.1 SPATIAL TRANSFORMS
452 9.6.2 GRAY LEVEL INTERPOLATION 455 9.6.3 THE GEOMETRIC RESTORATION
PROCEDURE 457 9.6.4 GEOMETRIC RESTORATION WITH CVIPTOOLS 458 9.7 KEY
POINTS 460 9.8 REFERENCES AND FURTHER READING 471 9.9 EXERCISES 473
9.9.1 PROGRAMMING EXERCISE: NOISE 478 9.9.2 PROGRAMMING EXERCISE: ORDER
FILTERS 479 9.9.3 PROGRAMMING EXERCISE: MEAN FILTERS 479 9.9.4
PROGRAMMING EXERCISE: MMSE FILTER 479 9.9.5 PROGRAMMING EXERCISE:
FREQUENCY DOMAIN FILTERS 479 9.9.6 PROGRAMMING EXERCISE: GEOMETRIC
TRANSFORMS 480 CHAPTER 10 IMAGE COMPRESSION 10.1 INTRODUCTION AND
OVERVIEW 481 10.1.1 COMPRESSION SYSTEM MODEL 485 10.2 LOSSLESS
COMPRESSION METHODS 489 10.2.1 HUFFMAN CODING 492 10.2.2 RUN-LENGTH
CODING 495 10.2.3 LEMPEL-ZIV-WELCH CODING 498 10.2.4 ARITHMETIC CODING
499 10.3 LOSSY COMPRESSION METHODS 500 10.3.1 GRAY-LEVEL RUN-LENGTH
CODING 501 10.3.2 BLOCK TRUNCATION CODING 504 10.3.3 VECTOR QUANTIZATION
509 10.3.4 DIFFERENTIAL PREDICTIVE CODING 513 10.3.5 MODEL-BASED AND
FRACTAL COMPRESSION 519 10.3.6 TRANSFORM CODING 521 10.3.7 HYBRID AND
WAVELET METHODS 527 10.4 KEY POINTS 534 10.5 REFERENCES AND FURTHER
READING 540 10.6 EXERCISES 541 10.6.1 PROGRAMMING EXERCISE:
SIGNAL-TO-NOISE RATIO AND ROOT-MEAN-SQUARE ERROR METRICS 546 10.6.2
PROGRAMMING EXERCISE: HUFFMAN CODING 546 10.6.3 PROGRAMMING EXERCISE:
RUN-LENGTH CODING 546 10.6.4 PROGRAMMING EXERCISE: BLOCK TRUNCATION
CODING 546 10.6.5 PROGRAMMING EXERCISE: DIFFERENTIAL PREDICTIVE CODING
546 10.6.6 PROGRAMMING EXERCISE: ZONAL CODING 547 SECTION IV PROGRAMMING
WITH CVIPTOOLS CHAPTER 11 CVIPLAB 11.1 INTRODUCTION TO CVIPLAB 551 11.2
TOOLKITS, TOOLBOXES AND APPLICATION LIBRARIES 556 11.3 COMPILING AND
LINKING CVIPLAB 557 11.3.1 HOW TO BUILD THE CVIPLAB PROJECT WITH
MICROSOFT'S VISUAL C++ 6.0 557 11.3.2 THE MECHANICS OF ADDING A FUNCTION
WITH MICROSOFT'S VISUAL C++ 6.0 559 11.3.3 USING CVIPLAB IN THE
PROGRAMMING EXERCISES 562 11.4 IMAGE DATA AND FILE STRUCTURES 566 11.5
CVIP PROJECTS 573 11.5.1 COMPUTER VISION PROJECTS 573 11.5.2 DIGITAL
IMAGE PROCESSING PROJECTS 574 CHAPTER 12 CVIPTOOLS C FUNCTION LIBRARIES
12.1 INTRODUCTION AND OVERVIEW 577 12.2 ARITHMETIC AND LOGIC
LIBRARY*ARITHLOGIC.LIB 577 12.3 BAND IMAGE LIBRARY*BAND.LIB 578 12.4
COLOR IMAGE LIBRARY*COLOR.LIB 578 12.5 COMPRESSION
LIBRARY*COMPRESSION.LIB 579 12.6 CONVERSION LIBRARY*CON VERSION, LIB 583
12.7 DISPLAY LIBRARY*DISPLAY.LIB 585 12.8 FEATURE EXTRACTION
LIBRARY*FEATURE.LIB 585 12.9 GEOMETRY LIBRARY*GEOMETRY.LIB 588 12.10
HISTOGRAM LIBRARY*HISTOGRAM.LIB 592 12.11 IMAGE LIBRARY*IMAGE.LIB 593
12.12 DATA MAPPING LIBRARY*MAPPING.LIB 594 12.13 MORPHOLOGICAL
LIBRARY*MORPHOLOGICAL.LIB 595 12.14 NOISE LIBRARY*NOISE.LIB 597 12.15
SEGMENTATION LIBRARY*SEGMENTATION.LIB 597 12.16 SPATIAL FILTER
LIBRARY*SPATIALFILTER.LIB 599 12.17 TRANSFORM LIBRARY*TRANSFORM.LIB 603
12.18 TRANSFORM FILTER LIBRARY*TRANSFORMFILTER.LIB 604 SECTION V
APPENDICES A. THE CVIPTOOLS CD-ROM 611 B. INSTALLING AND UPDATING
CVIPTOOLS 613 C. CVIPTOOLS C FUNCTIONS 617 D. CVIP RESOURCES 629 E.
CVIPTOOLS SOFTWARE ORGANIZATION 633 F. COMMON OBJECT MODULE (COM)
FUNCTIONS* CVIPTOOLS.DLL 635 INDEX 645 |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Umbaugh, Scott E. |
| author_facet | Umbaugh, Scott E. |
| author_role | aut |
| author_sort | Umbaugh, Scott E. |
| author_variant | s e u se seu |
| building | Verbundindex |
| bvnumber | BV021628007 |
| callnumber-first | T - Technology |
| callnumber-label | TA1634 |
| callnumber-raw | TA1634 |
| callnumber-search | TA1634 |
| callnumber-sort | TA 41634 |
| callnumber-subject | TA - General and Civil Engineering |
| classification_tum | DAT 760f |
| ctrlnum | (OCoLC)56412981 (DE-599)BVBBV021628007 |
| dewey-full | 006.4/2 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.4/2 |
| dewey-search | 006.4/2 |
| dewey-sort | 16.4 12 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| discipline_str_mv | Informatik |
| format | Book |
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| id | DE-604.BV021628007 |
| illustrated | Illustrated |
| index_date | 2024-07-02T14:55:57Z |
| indexdate | 2024-07-09T20:40:17Z |
| institution | BVB |
| isbn | 0849329191 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-014842953 |
| oclc_num | 56412981 |
| open_access_boolean | |
| owner | DE-91G DE-BY-TUM |
| owner_facet | DE-91G DE-BY-TUM |
| physical | 659 S. Ill., graph. Darst. 1 CD-ROM (12 cm) |
| publishDate | 2005 |
| publishDateSearch | 2005 |
| publishDateSort | 2005 |
| publisher | Taylor & Francis |
| record_format | marc |
| spelling | Umbaugh, Scott E. Verfasser aut Computer imaging digital image analysis and processing Scott E. Umbaugh Boca Raton [u.a.] Taylor & Francis 2005 659 S. Ill., graph. Darst. 1 CD-ROM (12 cm) txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references and index Computer vision Image processing Digital techniques Bildverarbeitung (DE-588)4006684-8 gnd rswk-swf Maschinelles Sehen (DE-588)4129594-8 gnd rswk-swf Maschinelles Sehen (DE-588)4129594-8 s Bildverarbeitung (DE-588)4006684-8 s DE-604 http://www.loc.gov/catdir/enhancements/fy0647/2004058331-d.html Publisher description HEBIS Datenaustausch Mainz application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014842953&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Umbaugh, Scott E. Computer imaging digital image analysis and processing Computer vision Image processing Digital techniques Bildverarbeitung (DE-588)4006684-8 gnd Maschinelles Sehen (DE-588)4129594-8 gnd |
| subject_GND | (DE-588)4006684-8 (DE-588)4129594-8 |
| title | Computer imaging digital image analysis and processing |
| title_auth | Computer imaging digital image analysis and processing |
| title_exact_search | Computer imaging digital image analysis and processing |
| title_exact_search_txtP | Computer imaging digital image analysis and processing |
| title_full | Computer imaging digital image analysis and processing Scott E. Umbaugh |
| title_fullStr | Computer imaging digital image analysis and processing Scott E. Umbaugh |
| title_full_unstemmed | Computer imaging digital image analysis and processing Scott E. Umbaugh |
| title_short | Computer imaging |
| title_sort | computer imaging digital image analysis and processing |
| title_sub | digital image analysis and processing |
| topic | Computer vision Image processing Digital techniques Bildverarbeitung (DE-588)4006684-8 gnd Maschinelles Sehen (DE-588)4129594-8 gnd |
| topic_facet | Computer vision Image processing Digital techniques Bildverarbeitung Maschinelles Sehen |
| url | http://www.loc.gov/catdir/enhancements/fy0647/2004058331-d.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014842953&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT umbaughscotte computerimagingdigitalimageanalysisandprocessing |