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Digital Image Processing An algorithmic introduction using Java
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Digital Image Processing An algorithmic introduction using Java
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Wilhelm Burger · Mark J. Burge
Digital Image Processing
An algorithmic introduction using Ja va
With 271 figures and 17 tables
2007
Springer
Berlin Heidelberg New York
Hongkong London
Mailand Paris Tokio
From: Burger, Burge: Digital Image Processing - An Algorithmic Approach using Java.
© 2008 Springer-Verlag New York. ISBN 978-1-84628-379-6, www.imagingbook.com
Contents
Preface ................................................... V
1 Crunching Pixels ..................................... 1
1.1 Programmingwith Images........................... 2
1.2 ImageAnalysisandComputerVision ................. 3
2 Digital Images ........................................ 5
2.1 TypesofDigitalImages ............................. 5
2.2 ImageAcquisition .................................. 5
2.2.1 ThePinhole CameraModel.................... 7
2.2.2 The“Thin” Lens ............................. 8
2.2.3 GoingDigital ................................ 8
2.2.4 Image SizeandResolution..................... 10
2.2.5 ImageCoordinateSystem ..................... 11
2.2.6 Pixel Values ................................. 11
2.3 ImageFileFormats................................. 13
2.3.1 RasterversusVectorData..................... 14
2.3.2 Tagged Image File Format (TIFF) . . . . . . . . . . . . . . 15
2.3.3 GraphicsInterchangeFormat(GIF) ............ 15
2.3.4 PortableNetworkGraphics (PNG) ............. 16
2.3.5 JPEG....................................... 17
2.3.6 WindowsBitmap(BMP)...................... 20
2.3.7 PortableBitmapFormat(PBM) ............... 21
2.3.8 AdditionalFileFormats....................... 21
2.3.9 Bits andBytes............................... 22
2.4 Exercises .......................................... 24
3ImageJ............................................... 27
3.1 ImageManipulation andProcessing................... 28
3.2 ImageJOverview................................... 28
3.2.1 KeyFeatures ................................ 29
3.2.2 InteractiveTools ............................. 30
3.2.3 ImageJPlugins .............................. 31
3.2.4 AFirstExample: InvertinganImage ........... 32
3.3 Additional Information on ImageJ and Java . . . . . . . . . . . . 35
3.3.1 Resourcesfor ImageJ ......................... 35
3.3.2 ProgrammingwithJava....................... 35
XI
From: Burger, Burge: Digital Image Processing - An Algorithmic Approach using Java.
© 2008 Springer-Verlag New York. ISBN 978-1-84628-379-6, www.imagingbook.com
Contents
3.4 Exercises .......................................... 36
4 Histograms ........................................... 37
4.1 What Is aHistogram?............................... 38
4.2 InterpretingHistograms ............................. 39
4.2.1 ImageAcquisition ............................ 40
4.2.2 ImageDefects................................ 42
4.3 ComputingHistograms.............................. 44
4.4 Histograms of Images with More than 8 Bits . . . . . . . . . . . 46
4.4.1 Binning ..................................... 46
4.4.2 Example .................................... 46
4.4.3 Implementation .............................. 47
4.5 ColorImageHistograms............................. 47
4.5.1 IntensityHistograms.......................... 48
4.5.2 Individual Color Channel Histograms . . . . . . . . . . . 48
4.5.3 CombinedColorHistogram.................... 49
4.6 CumulativeHistogram .............................. 50
4.7 Exercises .......................................... 51
5PointOperations..................................... 53
5.1 Modifying ImageIntensity........................... 54
5.1.1 ContrastandBrightness....................... 54
5.1.2 Limiting the Results byClamping .............. 54
5.1.3 InvertingImages ............................. 55
5.1.4 ThresholdOperation.......................... 55
5.2 Point OperationsandHistograms..................... 55
5.3 AutomaticContrastAdjustment...................... 57
5.4 Modified Auto-Contrast............................. 58
5.5 HistogramEqualization ............................. 59
5.6 HistogramSpecification ............................. 62
5.6.1 Frequencies and Probabilities . . . . . . . . . . . . . . . . . . 63
5.6.2 Principle of Histogram Specification . . . . . . . . . . . . 65
5.6.3 Adjusting to a Piecewise Linear Distribution . . . . . 65
5.6.4 Adjusting to a Given Histogram (Histogram
Matching)................................... 67
5.6.5 Examples ................................... 68
5.7 GammaCorrection ................................. 72
5.7.1 Why Gamma? ............................... 73
5.7.2 TheGammaFunction......................... 74
5.7.3 Real Gamma Values .......................... 74
5.7.4 Applications ofGamma Correction ............. 75
5.7.5 Implementation .............................. 76
5.7.6 Modified GammaCorrection................... 76
5.8 PointOperationsin ImageJ.......................... 80
5.8.1 Point Operations with Lookup Tables . . . . . . . . . . . 80
5.8.2 Arithmetic Operations ........................ 81
5.8.3 Point Operations Involving Multiple Images . . . . . 81
XII
From: Burger, Burge: Digital Image Processing - An Algorithmic Approach using Java.
© 2008 Springer-Verlag New York. ISBN 978-1-84628-379-6, www.imagingbook.com
Contents
5.8.4 Methods for Point Operations on Two Images . . . . 82
5.8.5 ImageJ Plugins for Multiple Images . . . . . . . . . . . . . 82
5.9 Exercises .......................................... 83
6 Filters ................................................ 87
6.1 What Is aFilter?................................... 87
6.2 LinearFilters ...................................... 89
6.2.1 The Filter Matrix ............................ 89
6.2.2 ApplyingtheFilter........................... 90
6.2.3 Computing theFilterOperation................ 91
6.2.4 FilterPlugin Examples........................ 92
6.2.5 IntegerCoefficients ........................... 93
6.2.6 FiltersofArbitrarySize....................... 94
6.2.7 TypesofLinearFilters........................ 95
6.3 FormalPropertiesof LinearFilters ................... 98
6.3.1 LinearConvolution ........................... 99
6.3.2 PropertiesofLinearConvolution ............... 100
6.3.3 Separability of Linear Filters . . . . . . . . . . . . . . . . . . . 101
6.3.4 Impulse Responseofa Filter................... 103
6.4 NonlinearFilters ................................... 104
6.4.1 MinimumandMaximumFilters................ 105
6.4.2 MedianFilter................................ 106
6.4.3 WeightedMedianFilter ....................... 107
6.4.4 OtherNonlinearFilters ....................... 110
6.5 ImplementingFilters................................ 111
6.5.1 Efficiency of FilterPrograms................... 111
6.5.2 Handling ImageBorders....................... 111
6.5.3 DebuggingFilter Programs.................... 112
6.6 FilterOperationsinImageJ.......................... 113
6.6.1 LinearFilters................................ 113
6.6.2 GaussianFilters.............................. 114
6.6.3 Nonlinear Filters ............................. 115
6.7 Exercises .......................................... 115
7 Edges and Contours .................................. 117
7.1 WhatMakesanEdge? .............................. 117
7.2 Gradient-BasedEdgeDetection ...................... 118
7.2.1 Partial Derivatives and the Gradient . . . . . . . . . . . . 119
7.2.2 Derivative Filters............................. 119
7.3 Edge Operators .................................... 120
7.3.1 Prewitt and SobelOperators................... 120
7.3.2 Roberts Operator ............................ 123
7.3.3 CompassOperators........................... 123
7.3.4 Edge Operatorsin ImageJ..................... 125
7.4 OtherEdge Operators .............................. 125
7.4.1 Edge Detection Based on Second Derivatives . . . . . 126
7.4.2 Edgesat Different Scales ...................... 126
XIII
From: Burger, Burge: Digital Image Processing - An Algorithmic Approach using Java.
© 2008 Springer-Verlag New York. ISBN 978-1-84628-379-6, www.imagingbook.com
Contents
7.4.3 Canny Operator.............................. 127
7.5 FromEdges toContours............................. 127
7.5.1 ContourFollowing............................ 127
7.5.2 EdgeMaps .................................. 129
7.6 Edge Sharpening ................................... 130
7.6.1 Edge Sharpening with the Laplace Filter . . . . . . . . 130
7.6.2 UnsharpMasking ............................ 133
7.7 Exercises .......................................... 137
8 Corner Detection ..................................... 139
8.1 Pointsof Interest................................... 139
8.2 HarrisCornerDetector.............................. 140
8.2.1 LocalStructureMatrix........................ 140
8.2.2 CornerResponseFunction (CRF) .............. 141
8.2.3 Determining Corner Points .................... 142
8.2.4 Example .................................... 142
8.3 Implementation .................................... 142
8.3.1 Step 1: Computing the Corner Response Function 144
8.3.2 Step 2: Selecting “Good” Corner Points . . . . . . . . . 148
8.3.3 Displaying theCornerPoints .................. 152
8.3.4 Summary.................................... 152
8.4 Exercises .......................................... 153
9 Detecting Simple Curves ............................. 155
9.1 SalientStructures .................................. 155
9.2 HoughTransform................................... 156
9.2.1 ParameterSpace ............................. 157
9.2.2 Accumulator Array ........................... 159
9.2.3 ABetterLine Representation.................. 159
9.3 Implementing the HoughTransform .................. 160
9.3.1 Filling the Accumulator Array . . . . . . . . . . . . . . . . . 161
9.3.2 AnalyzingtheAccumulatorArray .............. 163
9.3.3 Hough Transform Extensions . . . . . . . . . . . . . . . . . . 165
9.4 Hough Transform for Circles and Ellipses . . . . . . . . . . . . . . 167
9.4.1 CirclesandArcs ............................. 167
9.4.2 Ellipses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170
9.5 Exercises .......................................... 170
10 Morphological Filters ................................. 173
10.1 Shrink and Let Grow ............................... 174
10.1.1 NeighborhoodofPixels ....................... 175
10.2 BasicMorphologicalOperations...................... 175
10.2.1 The StructuringElement...................... 175
10.2.2 PointSets ................................... 176
10.2.3 Dilation..................................... 177
10.2.4 Erosion ..................................... 178
10.2.5 Properties of Dilation and Erosion . . . . . . . . . . . . . . 178
XIV
From: Burger, Burge: Digital Image Processing - An Algorithmic Approach using Java.
© 2008 Springer-Verlag New York. ISBN 978-1-84628-379-6, www.imagingbook.com
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