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4 of 4 people found the following review helpful:
4.0 out of 5 stars
More of an example book than a book on the theory,
This review is from: Introduction to Image Processing and Analysis (Hardcover)
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:
5.0 out of 5 stars
A must have book for image analysts,
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This review is from: Introduction to Image Processing and Analysis (Hardcover)
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.
2 of 4 people found the following review helpful:
2.0 out of 5 stars
Image Processing and Analysis falls short of its promise,
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Amazon Verified Purchase(What's this?)
This review is from: Introduction to Image Processing and Analysis (Hardcover)
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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Introduction to Image Processing and Analysis by John C. Russ (Hardcover - October 31, 2007)
$119.95
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