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Introduction to Image Processing and Analysis, by John C. Russ, J. Christian Russ
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Image processing comprises a broad variety of methods that operate on images to produce another image. A unique textbook, Introduction to Image Processing and Analysis establishes 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 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.
Homework problems are included in every chapter with solutions
available for download from the CRC Press website
The chapters work together to combine image processing with image analysis. The book begins with an explanation of familiar pixel array and goes on to describe the use of frequency space. Chapters 1 and 2 deal with the algorithms used in processing steps that are usually accomplished by a combination of measurement and processing operations, as described in chapters 3 and 4. The authors present each concept using a mixture of three mutually supportive tools: a description of the procedure with example images, the relevant mathematical equations behind each concept, and the simple source code (in C), which illustrates basic operations. In particularly, the source code provides a starting point to develop further modifications.
Written by John Russ, author of esteemed Image Processing Handbook now in its fifth edition, this book demonstrates functions to improve an image's of features and detail visibility, improve images for printing or transmission, and facilitate subsequent analysis.
- Sales Rank: #3081626 in Books
- Brand: Brand: CRC Press
- Published on: 2007-10-31
- Original language: English
- Number of items: 1
- Dimensions: 10.25" h x 7.50" w x .75" l, 1.94 pounds
- Binding: Hardcover
- 376 pages
- Used Book in Good Condition
Review
"Three titles from CRC Press look of interest, though I have not seen the books themselves. First, Introduction to Image Processing and Analysis by J.C. and J.C. Russ, which, says the flier, "establishes the programming involved in image processing and analysis by utilizing skills in C compiler and both Windows and MacOS programming environments… ."
―P.W. Hawkes in Ultramicroscopy 108 (2008)
About the Author
North Carolina State University, Raleigh, USA President/Technical Director, Reindeer Graphics
Most helpful customer reviews
6 of 6 people found the following review helpful.
More of an example book than a book on the theory
By calvinnme
This book is more of the "give a man a fish" than "teach a man to fish" variety. If you want something that gives you more of the theory but less in the way of examples I always recommend Digital Image Processing (3rd Edition). This book makes a good example book to parallel "Digital Image Processing". I already knew the theory pretty well when I picked this one up, but the explanations are rather brief here. What is very useful are the examples coded up in the C programming language. I highly recommend the book as a companion text or reference, but not as a primary means of learning image processing. Most of the examples will seem basic to someone who has much experience in the field, but there are a few interesting examples, particularly along the line of rolling your own Photoshop plug-ins, a subject that simply is not touched upon in most image processing books but can be an important topic.
The table of contents is not included in the product description so I do that next.
Introduction
Assumptions
The Program Environment
Image Values
Input and Output
Compiling a Function
Problems
The Authors
Adjusting Pixel Values 1
Optimizing Contrast 1
The Image Histogram 1
Other Color Coordinates 5
Maximizing Contrast 13
Nonlinear Stretching 19
Problems 23
Color Correction 24
Neutral Gray Methods 24
Color Filters 26
Tristimulus Correction 30
Problems 31
Correcting Nonuniform Illumination 32
Calculating a Correction 32
Measuring the Background 34
Problems 36
Geometric Transformations 36
Changing Image Size and Interpolation 36
Rotation 41
Alignment 45
Problems 48
Image Arithmetic 48
Adding and Subtracting 49
Multiplication and Division 51
Other Possibilities 52
Problems 55
Neighborhood Operations 57
Convolution 57
Neighborhoods and Kernels 57
Colors 60
Boundary Effects and Value Limits 63
Other Kernels 66
Uses of Gaussian Convolutions 72
More about Gaussians 79
Derivatives 80
Other Edge-Detecting Convolutions 85
Conditional or Adaptive Filters 88
Problems 90
Other Neighborhood Operations 91
Median Filter 91
Color Issues (Again) 98
Neighborhood Size and Shape 102
Noise 104
Ranking and Morphology 106
Top Hat Filter 108
Problems 113
Statistical Operations 116
The Variance Filter 116
Other Texture Filters 122
Enhancing Local Contrast 124
Problems 129
Image Processing in the Fourier Domain 131
The Fourier Transform 131
The Fourier Transform of an Image 133
Displaying the Transform Information 142
Low-Pass Filters 145
High-Pass and Band-Pass Filters 150
Problems 154
Removing Periodic Noise 154
Masks for Selected Frequencies 155
Measurements 158
Problems 160
Convolution and Correlation 161
Convolution in the Fourier Domain 161
Correlation 163
Problems 166
Deconvolution 167
Wiener Deconvolution 167
The Point Spread Function 171
Problems 174
Other Transform Domains 174
The Wavelet Transform 174
Problems 180
Compression 180
Lossless Compression 181
JPEG Compression 184
Fourier and Wavelet Compression 188
Problems 190
Binary Images 193
Thresholding 193
Basics of Thresholding 195
Histogram-Based Thresholding 195
Other Criteria 206
Color Images 209
Problems 214
Morphological Processing 214
Classic Opening and Closing 215
The Euclidean Distance Map 220
Problems 227
Other Morphological Operations 228
Ultimate Points and Watersheds 228
Skeletons 231
Outlines and Holes 239
Problems 241
Boolean Operations 241
Multiple Criteria for Selection 242
Grids for Measurements 244
Other Combinations 247
Problems 253
Measurements 255
Global Measurements 255
Area and Perimeter 256
Number of Features 262
Counting and Image Boundaries 267
Measurements with Grids 270
Problems 273
Feature Measurements 276
Size 276
Position 281
Shape 287
Density and Color Measurement 293
Problems 299
Classification 300
Multiple Criteria 300
Problems 304
Software 307
The Plug-In Source Code 307
The Project Folder 308
C versus C++ versus Other Languages 309
Building a Project 309
What Photoshop Looks for from a Plug-In 310
PiPLs - Adobe's Plug-In Property Lists 311
Debugging 312
Anatomy of a Plug-In 313
The Main Loop 313
Memory Allocation 314
Accessing Pixel Data 314
The Reference Image 315
Temporary Images 316
Reading and Writing Data Files 317
Writing to a Text File 318
Reading from a Text File 318
Escape/Cancel/Abort and the Progress Bar 319
Error Handling 320
Inside the Glue Code 321
Structures 321
General Routines 322
Accessing the Current Image 325
Accessing a Semi-Permanent Reference Image 326
Creating and Accessing Temporary Images in Memory 327
Errors 328
The Photoshop Interface 328
Adobe's Plug-In API and the Tiny Portion Used in this Text 329
Data Structures 329
Adobe Constants 330
The Calling Sequence 330
Callbacks 331
Pixel Ranges Depend on Modes 331
LAB to RGB Translation 332
Unsupported Modes 332
Lines versus Tiles 333
Full API Summary 333
References and Literature 337
Index 343
2 of 3 people found the following review helpful.
A must have book for image analysts
By Kenneth J. Hoerricks
An absolute must have book from this father/son duo. The examples are easy to follow and duplicate on your own. Once you've mastered the examples, you are open to trying some tricks on your own. This is the perfect compliment to Forensic Photoshop or any forensic imaging workflow.
5 of 8 people found the following review helpful.
Image Processing and Analysis falls short of its promise
By Richard J. Nolde
I purchased this book on the recommendation of a fellow software developer. It covers a wide variety of topics related to Image Processing. The text is readable and there are numerous sample images in black and white plus a color plate section that reproduces the more important images in color as appropriate. I have two serious complaints about the book. First, the sample code is abysmally error prone and at times wrong. It is hard to tell the typos from the incorrect code. Second, the model used by the authors is to create Photoshop plugins so that the basic IO functions and presentation logic are hidden from the user. This makes the book essentially useless for anyone not developing on Winders and paying the Photo$hop license fees. If the sample code were accurate, and more than the barest of pseudocode, it could be useful to a much wider audience, but it isn't. This is too bad since the discussions and illustrations suggest that there could be real worth in the text but it is a real slog to separate the wheat from the chaff.
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