Introduction to Image Processing and Analysis

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ISBN: 9780849370731 | 0849370736
Cover: Hardcover
Copyright: 10/31/2007

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A unique textbook,Introduction to Image Processing and Analysisexplores the programming involved in image processing and analysis by utilizing skills in C compiler and both Windows and MacOS programming environments. The provided mathematical background illustrates the workings of algorithms and emphasizes the practical reasons for using certain methods, their effects on images, and their appropriate applications. The chapters work together to combine image processing with image analysis. The text concentrates on image processing and measurement and details the implementation of many of the most widely used and most important image processing and analysis algorithms.

Introduction	p. xi
Assumptions	p. xi
The Program Environment	p. xi
Image Values	p. xiii
Input and Output	p. xvii
Compiling a Function	p. xvii
Problems	p. xviii
The Authors	p. xix
Adjusting Pixel Values	p. 1
Optimizing Contrast	p. 1
The Image Histogram	p. 1
Other Color Coordinates	p. 5
Maximizing Contrast	p. 13
Nonlinear Stretching	p. 19
Problems	p. 23
Color Correction	p. 24
Neutral Gray Methods	p. 24
Color Filters	p. 26
Tristimulus Correction	p. 30
Problems	p. 31
Correcting Nonuniform Illumination	p. 32
Calculating a Correction	p. 32
Measuring the Background	p. 34
Problems	p. 36
Geometric Transformations	p. 36
Changing Image Size and Interpolation	p. 36
Rotation	p. 41
Alignment	p. 45
Problems	p. 48
Image Arithmetic	p. 48
Adding and Subtracting	p. 49
Multiplication and Division	p. 51
Other Possibilities	p. 52
Problems	p. 55
Neighborhood Operations	p. 57
Convolution	p. 57
Neighborhoods and Kernels	p. 57
Colors	p. 60
Boundary Effects and Value Limits	p. 63
Other Kernels	p. 66
Uses of Gaussian Convolutions	p. 72
More about Gaussians	p. 79
Derivatives	p. 80
Other Edge-Detecting Convolutions	p. 85
Conditional or Adaptive Filters	p. 88
Problems	p. 90
Other Neighborhood Operations	p. 91
Median Filter	p. 91
Color Issues (Again)	p. 98
Neighborhood Size and Shape	p. 102
Noise	p. 104
Ranking and Morphology	p. 106
Top Hat Filter	p. 108
Problems	p. 113
Statistical Operations	p. 116
The Variance Filter	p. 116
Other Texture Filters	p. 122
Enhancing Local Contrast	p. 124
Problems	p. 129
Image Processing in the Fourier Domain	p. 131
The Fourier Transform	p. 131
The Fourier Transform of an Image	p. 133
Displaying the Transform Information	p. 142
Low-Pass Filters	p. 145
High-Pass and Band-Pass Filters	p. 150
Problems	p. 154
Removing Periodic Noise	p. 154
Masks for Selected Frequencies	p. 155
Measurements	p. 158
Problems	p. 160
Convolution and Correlation	p. 161
Convolution in the Fourier Domain	p. 161
Correlation	p. 163
Problems	p. 166
Deconvolution	p. 167
Wiener Deconvolution	p. 167
The Point Spread Function	p. 171
Problems	p. 174
Other Transform Domains	p. 174
The Wavelet Transform	p. 174
Problems	p. 180
Compression	p. 180
Lossless Compression	p. 181
JPEG Compression	p. 184
Fourier and Wavelet Compression	p. 188
Problems	p. 190
Binary Images	p. 193
Thresholding	p. 193
Basics of Thresholding	p. 195
Histogram-Based Thresholding	p. 195
Other Criteria	p. 206
Color Images	p. 209
Problems	p. 214
Morphological Processing	p. 214
Classic Opening and Closing	p. 215
The Euclidean Distance Map	p. 220
Problems	p. 227
Other Morphological Operations	p. 228
Ultimate Points and Watersheds	p. 228
Skeletons	p. 231
Outlines and Holes	p. 239
Problems	p. 241
Boolean Operations	p. 241
Multiple Criteria for Selection	p. 242
Grids for Measurements	p. 244
Other Combinations	p. 247
Problems	p. 253
Measurements	p. 255
Global Measurements	p. 255
Area and Perimeter	p. 256
Number of Features	p. 262
Counting and Image Boundaries	p. 267
Measurements with Grids	p. 270
Problems	p. 273
Feature Measurements	p. 276
Size	p. 276
Position	p. 281
Shape	p. 287
Density and Color Measurement	p. 293
Problems	p. 299
Classification	p. 300
Multiple Criteria	p. 300
Problems	p. 304
Software	p. 307
The Plug-In Source Code	p. 307
The Project Folder	p. 308
C versus C++ versus Other Languages	p. 309
Building a Project	p. 309
What Photoshop Looks for from a Plug-In	p. 310
PiPLs - Adobe's Plug-In Property Lists	p. 311
Debugging	p. 312
Anatomy of a Plug-In	p. 313
The Main Loop	p. 313
Memory Allocation	p. 314
Accessing Pixel Data	p. 314
The Reference Image	p. 315
Temporary Images	p. 316
Reading and Writing Data Files	p. 317
Writing to a Text File	p. 318
Reading from a Text File	p. 318
Escape/Cancel/Abort and the Progress Bar	p. 319
Error Handling	p. 320
Inside the Glue Code	p. 321
Structures	p. 321
General Routines	p. 322
Accessing the Current Image	p. 325
Accessing a Semi-Permanent Reference Image	p. 326
Creating and Accessing Temporary Images in Memory	p. 327
Errors	p. 328
The Photoshop Interface	p. 328
Adobe's Plug-In API and the Tiny Portion Used in this Text	p. 329
Data Structures	p. 329
Adobe Constants	p. 330
The Calling Sequence	p. 330
Callbacks	p. 331
Pixel Ranges Depend on Modes	p. 331
LAB to RGB Translation	p. 332
Unsupported Modes	p. 332
Lines versus Tiles	p. 333
Full API Summary	p. 333
References and Literature	p. 337
Index	p. 343
Table of Contents provided by Ingram. All Rights Reserved.

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Introduction to Image Processing and Analysis

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