## Principles of Digital Image Processing: Core AlgorithmsThis is the second volume of a book series that provides a modern, algori- mic introduction to digital image processing. It is designed to be used both by learners desiring a ?rm foundation on which to build and practitioners in search of critical analysis and modern implementations of the most important techniques. This updated and enhanced paperback edition of our compreh- sive textbook Digital Image Processing: An Algorithmic Approach Using Java packages the original material into a series of compact volumes, thereby s- porting a ?exible sequence of courses in digital image processing. Tailoring the contents to the scope of individual semester courses is also an attempt to p- vide a?ordable (and “backpack-compatible”) textbooks without comprimising the quality and depth of content. This second volume, titled Core Algorithms, extends the introductory - terial presented in the ?rst volume (Fundamental Techniques) with additional techniques that are, nevertheless, part of the standard image processing to- box. A forthcomingthird volume(Advanced Techniques) will extendthis series and add important material beyond the elementary level, suitable for an - vanced undergraduate or even graduate course. |

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### Contents

1 | |

2 | |

3 | |

5 | |

6 | |

22 Region Contours | 17 |

23 Representing Image Regions | 26 |

24 Properties of Binary Regions | 32 |

73 The Discrete Fourier Transform DFT | 144 |

74 Implementing the DFT | 154 |

75 Exercises | 156 |

The Discrete Fourier Transform in 2D | 157 |

82 Visualizing the 2D Fourier Transform | 162 |

83 Frequencies and Orientation in 2D | 164 |

84 2D Fourier Transform Examples | 171 |

85 Applications of the DFT | 175 |

25 Exercises | 46 |

Detecting Simple Curves | 49 |

32 Hough Transform | 50 |

33 Implementing the Hough Transform | 55 |

34 Hough Transform for Circles and Ellipses | 63 |

35 Exercises | 67 |

Corner Detection | 69 |

42 Harris Corner Detector | 70 |

43 Implementation | 72 |

44 Exercises | 84 |

Color Quantization | 85 |

51 Scalar Color Quantization | 86 |

52 Vector Quantization | 88 |

53 Exercises | 95 |

Colorimetric Color Spaces | 96 |

61 CIE Color Spaces | 98 |

62 CIE Lab | 104 |

63 sRGB | 106 |

64 Adobe RGB | 111 |

66 Colorimetric Support in Java | 114 |

67 Exercises | 124 |

Introduction to Spectral Techniques | 125 |

71 The Fourier Transform | 126 |

72 Working with Discrete Signals | 137 |

86 Exercises | 180 |

The Discrete Cosine Transform DCT | 183 |

92 TwoDimensional DCT | 187 |

93 Other Spectral Transforms | 188 |

94 Exercises | 190 |

Geometric Operations | 191 |

101 2D Mapping Function | 193 |

102 Resampling the Image | 209 |

103 Interpolation | 210 |

104 Java Implementation | 238 |

105 Exercises | 253 |

Comparing Images | 255 |

111 Template Matching in Intensity Images | 257 |

112 Matching Binary Images | 269 |

113 Exercises | 278 |

Mathematical Notation | 279 |

A2 Set Operators | 281 |

A3 Complex Numbers | 282 |

Source Code | 283 |

B2 Harris Corner Detector | 294 |

B3 MedianCut Color Quantization | 301 |

313 | |

320 | |

### Other editions - View all

Principles of Digital Image Processing: Fundamental Techniques Wilhelm Burger,Mark J. Burge Limited preview - 2010 |

Principles of Digital Image Processing: Fundamental Techniques Wilhelm Burger,Mark J. Burge No preview available - 2011 |

### Common terms and phrases

accumulator array affine transformation algorithm aliasing angle arbitrary basis functions bicubic interpolation bilinear bilinear interpolation binary image Binary Region Catmull-Rom chain code chamfer coefficient color quantization color space ColorBox components computed coordinates corner points correlation corresponding cubic defined described Digital Image Processing direction discrete discrete signal distance transform double edge end of class example Exercise Figure filter float FloatProcessor Flood Filling foreground pixel Fourier spectrum Fourier transform frequency space function g(x Hough transform image point ImageJ ImageProcessor import inner contour interpolation kernel inverse Java Kmax LinearMapping match matrix maximum median-cut nonlinear one-dimensional orientation original image parameter space Point2D position quadrilaterals quantization reference image region labeling resulting RGB color RGB color space rmax rotation sampling frequency search image signal sine functions specified spectral sRGB static step template two-dimensional vector wave number white point windowing function XYZ color