Digital Image ProcessingThe sixth edition of this worldwide used textbook was thoroughly - vised and extended. Throughout the whole text you will ?nd numerous improvements, extensions, and updates. Above all, I would like to draw your attention to two major changes. Firstly, the whole textbook is now clearly partitioned into basic and advanced material in order to cope with the ever-increasing ?eld of di- talimageprocessing. Themostimportantequationsareputintoframed boxes. The advanced sections are located in the second part of each chapter and are marked by italic headlines and by a smaller typeface. In this way, you can ?rst work your way through the basic principles of digital image processing without getting overwhelmed by the wealth of the material. You can extend your studies later to selected topics of interest. The second most notable extension are exercises that are now - cluded at the end of each chapter. These exercise help you to test your understanding, train your skills, and introduce you to real-world image processing tasks. The exercises are marked with one to three stars to indicate their di?culty. An important part of the exercises is a wealth of interactive computer exercises, which cover all topics of this te- book. These exercises are performed with the image processing so- ware heurisko® (http://www. heurisko. de), which is included on the accompanying CD-ROM. In this way you can get own practical expe- ence with almost all topics and algorithms covered by this book. |
Contents
| 3 | |
Image Representation | 30 |
7 | 77 |
1 | 105 |
Neighborhood Operations | 135 |
Quantitative Visualization 157 | 155 |
Image Formation | 189 |
Digitization Sampling Quantization | 243 |
Simple Neighborhoods 359 | 358 |
Motion | 397 |
Texture | 435 |
Segmentation | 449 |
Regularization and Modeling | 463 |
Morphology | 501 |
Shape Presentation and Analysis | 515 |
Classification | 533 |
Pixel Processing | 257 |
Averaging | 299 |
Edges | 331 |
A Reference Material | 553 |
B Notation | 577 |
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Common terms and phrases
according to Eq algorithm amplitude analysis angle applied B-spline binomial box filter camera coefficients color complex components compute constant corresponding denoted depth derivative filters detection deviation digital image processing direction discrete displacement vector distance distribution edge edge detection eigenvalue equation error example factor Figure filter mask first-order Fourier descriptors Fourier domain Fourier space Fourier transform Gaussian geometric gradient gray value illumination image plane image sequences Interactive demonstration interpolation inverse Jähne linear magnitude matrix mean measure motion multiplication neighborhood noise nonlinear object optical flow optical system orientation parameters phase pixels point operations point spread function problem projection properties pyramid quadrature filter quantization radiance radiation recursive filters representation resolution rotation sampling scale space segmentation shift shows signal spatial square structure tensor surface symmetry techniques texture theorem tion transfer function variance vector wave number wavelength zero