introduction. 1
preview 1
1.1 background 1
1.2 what is digital image processing? 2
1.3 background on matlab and the image processing toolbox
1.4 areas of image processing covered in the book 5
1.5 the book web site 6
1.6 notation 7
1.7 the matlab working environment 7
1.8 how references are organized in the book 11
summary 11
2 fundamentals 12
preview 12
2.1 digital image representation 12
2.2 reading images 14
2.3 displaying images 16
2.4 writing images 18
2.5 data classes 23
2.6 image types 24
2.7 converting between data classes and image types 25
.2.8 array indexing 30
2.9 some important standard arrays 37
2.10 introduction to m-function programming 38
3 intensity transformations
and spatial filtering 65
preview 65
3.1 background 65
3.2 intensity transformation functions 66
3.3 histogram processing and function plotting 76
3.4 spatial filtering 89
3.5 image processing toolbox standard spatial filters 99
4 frequency domain processing 108
preview 108
4.1 the 2-d discrete fourier transform 108
4.2 computing and visualizing the 2-d dft in matlab 112
4.3 filtering in the frequency domain 115
4.4 obtaining frequency domain filters from spatial filters 122
4.5 generating filters directly in the frequency domain 127
image restoration 141
preview 141
5.1 a model of the image degradation/restoration process 142
5.2 noise models 143
5.3 restoration in the presence of noise only—spatial filtering
5.4 periodic noise reduction by frequency domain filtering
5.5 modeling the degradation function 166
5.6 direct inverse filtering 169
5.7 wiener filtering 170
5.8 constrained least squares (regularized) filtering 173
5.9 iterative nonlinear restoration using the lucy-richardson
algorithm 176
5.10 blind deconvolution 179
5.11 geometric transformations and image regist_ration 182
6 color image processing 194
preview 194
6.1 color image representation in matlab.. 194
6.2 converting to other color spaces 204
6.3 the basics of color image processing 215
6.4 color transformations 216
6.5 spatial filtering of color images 227
6.6 working directly in rgb vector space 231
wavelets 242
preview 242
7.1 background 242
7.2 the fast wavelet transform 245
7.3 working with wavelet decomposition structures 259
7.4 the inverse fast wavelet transform 271
7.5 wavelets in image processing 276
image compression 282
preview 282
8.1 background 283
8.2 coding redundancy 286
8.3 interpixel redundancy 309
8.4 psychovisual redundancy 315
8.5 jpeg compression 317
9 morphological image processing 334
preview 334
9.1 preliminaries 335
9.2 dilation and erosion 337
9.3 combining dilation and erosion 347
9.4 labeling connected components 359
9.5 morphological reconstruction 362
9.6 gray-scale morphology 366
10 image segmentation 378
preview 378
10.1 point, line, and edge detection 379
10.2 line detection using the hough transform 393
10.3 thresholding 404
10.4 region-based segmentation 407
10.5 segmentation using the watershed transform 417
11 representation and description 426
preview 426
11.1 background 426
11.2 representation 436
11.3 boundary descriptors 455
11.4 regional descriptors 463
11.5 using principal components for description 474
summary 483
12 object recognition 484
preview 484
12.1 background 484
12.2 computing distance measures in matlab 485
12.3 recognition based on decision-theoretic methods 488
12.4 structural recognition 498
appendixa function summary 514
appendixb ice and matlab graphical user interfaces 527
appendix c m-functions 552
bibliography 594
index... 597
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