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Computer imaging: digital image analysis and processing

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Bibliographic Details
Main Author:	Umbaugh, Scott E. (Author)
Format:	Book
Language:	English
Published:	Boca Raton [u.a.] Taylor & Francis 2005
Subjects:	Computer vision Image processing > Digital techniques Bildverarbeitung Maschinelles Sehen
Online Access:	Publisher description Inhaltsverzeichnis
Item Description:	Includes bibliographical references and index
Physical Description:	659 S. Ill., graph. Darst. 1 CD-ROM (12 cm)
ISBN:	0849329191

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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 DETECTIONROBERTS 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 DOMAINTHE POINT SPREAD FUNCTION 431 9.4.2 THE FREQUENCY DOMAINTHE 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 LIBRARYARITHLOGIC.LIB 577 12.3 BAND IMAGE LIBRARYBAND.LIB 578 12.4 COLOR IMAGE LIBRARYCOLOR.LIB 578 12.5 COMPRESSION LIBRARYCOMPRESSION.LIB 579 12.6 CONVERSION LIBRARYCON VERSION, LIB 583 12.7 DISPLAY LIBRARYDISPLAY.LIB 585 12.8 FEATURE EXTRACTION LIBRARYFEATURE.LIB 585 12.9 GEOMETRY LIBRARYGEOMETRY.LIB 588 12.10 HISTOGRAM LIBRARYHISTOGRAM.LIB 592 12.11 IMAGE LIBRARYIMAGE.LIB 593 12.12 DATA MAPPING LIBRARYMAPPING.LIB 594 12.13 MORPHOLOGICAL LIBRARYMORPHOLOGICAL.LIB 595 12.14 NOISE LIBRARYNOISE.LIB 597 12.15 SEGMENTATION LIBRARYSEGMENTATION.LIB 597 12.16 SPATIAL FILTER LIBRARYSPATIALFILTER.LIB 599 12.17 TRANSFORM LIBRARYTRANSFORM.LIB 603 12.18 TRANSFORM FILTER LIBRARYTRANSFORMFILTER.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 DETECTIONROBERTS 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 DOMAINTHE POINT SPREAD FUNCTION 431 9.4.2 THE FREQUENCY DOMAINTHE 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 LIBRARYARITHLOGIC.LIB 577 12.3 BAND IMAGE LIBRARYBAND.LIB 578 12.4 COLOR IMAGE LIBRARYCOLOR.LIB 578 12.5 COMPRESSION LIBRARYCOMPRESSION.LIB 579 12.6 CONVERSION LIBRARYCON VERSION, LIB 583 12.7 DISPLAY LIBRARYDISPLAY.LIB 585 12.8 FEATURE EXTRACTION LIBRARYFEATURE.LIB 585 12.9 GEOMETRY LIBRARYGEOMETRY.LIB 588 12.10 HISTOGRAM LIBRARYHISTOGRAM.LIB 592 12.11 IMAGE LIBRARYIMAGE.LIB 593 12.12 DATA MAPPING LIBRARYMAPPING.LIB 594 12.13 MORPHOLOGICAL LIBRARYMORPHOLOGICAL.LIB 595 12.14 NOISE LIBRARYNOISE.LIB 597 12.15 SEGMENTATION LIBRARYSEGMENTATION.LIB 597 12.16 SPATIAL FILTER LIBRARYSPATIALFILTER.LIB 599 12.17 TRANSFORM LIBRARYTRANSFORM.LIB 603 12.18 TRANSFORM FILTER LIBRARYTRANSFORMFILTER.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
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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
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