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Welcome to my new book "digital image processing technology and Visual: C++ practice"

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Digital image processing technology and the practice of C++ Visual:




The digital image processing: Technology detailed and Visual C + + practice "comprehensive systematically about digital image processing in the field of 15 core topics, including color space, image coding, frequency domain transform, image file format, geometric transform, gray-scale transformation, image enhancement processing, edge detection, contour tracking, morphological processing, image segmentation, image encryption and hiding, wavelet transform, partial differential equations and image denoising. In order to facilitate the learning and practice, based on the self-developed platform magichouse, this book provides the complete coding algorithms which are realized, and under the environment of Visual C + + 2005 debugging through. This book to readers a comprehensive detailed introduction of technologies and methods of digital image processing programming under c++ visual.


Author: Zuo Fei
Publisher: Publishing House of electronics industry
ISBN:9787121224836
Time: 2014-3-27
Publication date: March 2014
Format: 16
Page number: 591
Revision: 1-1

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Catalog
"Digital image processing technology and visual: c++ practice"
The first chapter is introduction 1
1.1 overview of digital image processing 1
1.1.1 image and digital image 1
1.1.2 digital image processing research content 3
Application of 1.1.3 digital image processing 5
1.2 c++ visual overview 6
Visual c++ 1.2.1 profile 6
1.2.2 excellent integrated development environment 9
1.3 processing digital images in c++ visual 12
1.3.1 bitmap and palette 13
1.3.2 graphics device interface 14
1.4 examples of this chapter: the use of c++ visual drawing program 16
1.4.1 instance preview 16
1.4.2 started to create the project 17
1.4.3 completed an instance of encoding 19
The second chapter color system 25
2.1 learning image processing from the beginning of the understanding of color 25
2.1.1 what is the color 25
2.1.2 color properties 27
Energy distribution of 2.1.3 light source 28
2.2 CIE color chart 30
The establishment of CIE 2.2.1 color model 30
CIE 2.2.2 understanding of the color map 32
Subsequent development of CIE 2.2.3 color map 33
2.3 commonly used color space 34
RGB 2.3.1 color space 34
Cmy/cmyk 2.3.2 color space 35
Hsv/hsb 2.3.3 color space 37
Hsi/hsl 2.3.4 color space 38
Lab 2.3.5 color space 40
Yuv/ycbcr 2.3.6 color space 40
2.4 color space conversion method 41
RGB 2.4.1 conversion to HSV method 42
RGB 2.4.2 conversion to HSI method 42
RGB 2.4.3 conversion to YUV method 44
RGB 2.4.4 conversion to YCbCr method 45
2.5 examples of this chapter: the implementation of the Photoshop Color Editor 46
2.5.1 some problems to be solved 46
2.5.2 started to create the project 48
2.5.3 completed an instance of encoding 49
The third chapter of the image transform and encoding 51
3.1 image encoding's theoretical basis 51
3.1.1 rate distortion function 51
3.1.2 Shannon under the border 60
3.1.3 no memory Gauss source 63
3.1.4 has memory Gauss source 67
3.2 image compression encoding 74
3.2.1 encoding 74
LZW 3.2.2 encoding 75
3.2.3 Hoffman encoding 77
3.3 Fu Liye transform 83
The mathematical basis of 3.3.1 Fu Liye transform 83
Relationship between 3.3.2 Fu Liye transform and Fu Liye series 86
3.3.3 digital image of the Fourier transform 92
3.3.4 fast Fu Liye transform algorithm 94
3.3.5 programming to achieve the image of the fast Fu Liye transform 99
3.4 discrete cosine transform 105
3.4.1 basic concepts and mathematical description 105
The significance of 3.4.2 discrete cosine transform 107
Implementation of 3.4.3 discrete cosine transform 109
3.5 sons with encoding 111
3.5.1 digital signal processing based on 112
3.5.2 multi sample rate signal processing 115
Subband decomposition of 3.5.3 image 124
In the fourth chapter, we use DIB to process digital image 130
4.1 device dependent bitmap and device independent bitmap 130
4.1.1 device related bitmap (DDB) 130
4.1.2 device independent bitmap (DIB) 130
4.2 CBitmap class 131
4.2.1 create DDB 131
Member function in CBitmap 4.2.2 133
4.2.3 application DDB display image 134
4.2.4 application DDB display large image 135
4.3 further understanding of DIB 143
Structure of DIB 4.3.1 143
DIB 4.3.2 information section 143
4.3.3 bitmap data 145
4.3.4 and DIB related functions 145
4.4 examples of this chapter: DIB class package 147
4.4.1 class abstraction and design 148
4.4.2 write constructor 150
DIB 4.4.3 bitmap display 154
BMP 4.4.4 file storage 155
In the fifth chapter, we use gdi+ to process digital image 157
5.1 gdi+ profile 157
Gdi+ 5.1.1 overview 157
Structure of gdi+ 5.1.2 158
The configuration of gdi+ 5.1.3 in c++ visual 158 2005
5.2 gdi+ based 160
Graphics 5.2.1 class 160
The basic data type of gdi+ 5.2.2 162
Color in gdi+ 5.2.3 164
5.3 basic methods of gdi+ image processing 165
Gdi+ 5.3.1 image class 166
5.3.2 create image object 167
5.3.3 image display and zoom 169
The basic processing method of 5.3.4 image 174
5.4 image cut 182
5.4.1 clipping region 182
GraphicsPath 5.4.2 class 183
Region 5.4.3 class 187
5.5 the color of the image processing 191
ColorMatrix 5.5.1 structure 191
5.5.2 to change the transparency of the image 192
5.5.3 will be converted to grayscale images 196
5.5.4 to change the brightness of the image 198
5.5.5 to change the image contrast 200
5.6 examples of this chapter: similar to the ACDSee image browsing tool 202
5.6.1 instance preview 203
5.6.2 outline design 203
5.6.3 completed an instance of encoding 208
Sixth chapter image file format 212
6.1 overview of image files 212
6.1.1 image file 212
The general structure of the 6.1.2 image file 213
6.1.3 image file common parameters 213
6.2 BMP file format 215
6.2.1 file structure 215
6.2.2 file header and header 215
6.2.3 main parameters 216
6.3 GIF file format 216
Gif 6.3.1 format 216
Gif 6.3.2 file structure 217
Gif 6.3.3 file block structure 218
6.3.4 play GIF animation under gdi+ 222
6.4 PNG file format 227
Png 6.4.1 format 227
Png 6.4.2 file structure 227
Key data blocks in PNG 6.4.3 229
6.5 JPEG file and its coding and decoding implementation 230
JPEG 6.5.1 document overview 230
Coding and decoding principle of JPEG 6.5.2 230
JPEG 6.5.3 file format 239
JPEG 6.5.4 decoding process to achieve 242
The seventh chapter of the image point operations 248
7.1 gray histogram 248
7.1.1 histogram profile 248
7.1.2 basic principles 250
7.1.3 programming 250
7.2 gray linear transformation 259
7.2.1 basic principles 259
7.2.2 programming 262
7.3 gray level nonlinear transformation 265
7.3.1 gray scale logarithmic transformation 265
7.3.2 gray power transformation 269
7.3.3 gray scale transformation 271
7.4 gray threshold transform 273
7.4.1 basic principles 273
7.4.2 programming 274
7.5 gray stretch 276
7.5.1 basic principles 276
7.5.2 programming 278
7.6 gray balance 282
7.6.1 basic principles 283
7.6.2 programming 284
In the eighth chapter, the geometric transformation of the image is 286
8.1 basic theory of image geometric transformation 286
8.1.1 image geometric transformation overview 286
Mathematical description of geometric transformation of 8.1.2 image 289
8.2 image translation transform 289
8.2.1 effect preview 289
8.2.2 basic principles 290
8.2.3 programming 291
8.3 image transform 295
8.3.1 effect preview 295
8.3.2 basic principles 296
8.3.3 programming 297
8.4 image transpose 300
8.4.1 effect preview 300
8.4.2 basic principles 300
8.4.3 programming 301
8.5 image zoom 303
8.5.1 effect preview 303
8.5.2 basic principles 304
Introduction of 8.5.3 interpolation algorithm 305
8.5.4 programming 307
8.6 rotation of the image 312
8.6.1 effect preview 312
8.6.2 basic principles 313
8.6.3 programming 316
8.7 using gdi+ to achieve the geometric transformation of the image 322
Gdi+ 8.7.1 transform operation 323
8.7.2 translation 324
8.7.3 zoom 326
8.7.4 rotation 327
Combination of 8.7.5 transform 331
8.7.6 use the matrix to carry out other geometric transformation 333
The ninth chapter image enhancement processing 337
9.1 convolution integral and neighborhood processing 337
9.1.1 understand the concept of convolution integral 337
9.1.2 convolution should be applied to the principle of image processing 342
Basic concepts of 9.1.3 neighborhood processing 342
9.2 simple smooth image 345
9.2.1 image of a simple smooth principle 345
9.2.2 image simple and smooth algorithm to achieve 346
9.3 image Gauss smooth 350
9.3.1 smooth linear filter 350
9.3.2 Gauss smooth principle 351
9.3.3 Gauss distribution 352
9.3.4 Gauss smoothing algorithm to achieve 354
9.4 image median filter 358
9.4.1 statistical sorting filter 358
9.4.2 image median filtering principle 359
9.4.3 image median filtering algorithm to achieve 361
9.5 Laplasse image sharpening 367
9.5.1 image sharpening 367
9.5.2 Laplasse sharpening principle 367
9.5.3 Laplasse sharpening algorithm to achieve 368
9.6 Sobel edge thinning 372
The principle of edge thinning of Sobel 9.6.1 372
Sobel 9.6.2 edge thinning algorithm to achieve 375
Morphological processing of the image in the tenth chapter 381
10.1 mathematical morphology 381
10.2 some of the necessary concepts and symbols 381
10.3 corrosion of the image 385
10.3.1 corrosion principle 385
10.3.2 programming 388
10.4 expansion of the image 393
10.4.1 expansion principle 393
10.4.2 programming 395
10.5 the properties and applications of corrosion and expansion 399
Algebraic properties of 10.5.1 corrosion and expansion 399
Application of 10.5.2 corrosion and expansion 401
10.6 open operation and close operation 407
10.6.1 open operation 407
10.6.2 closed operation 409
10.6.3 programming 410
Algebraic properties of 10.6.4 open and closed operations 411
10.7 other operations of image morphology 413
10.7.1 hit / miss operation 413
10.7.2 refinement processing 416
The eleventh chapter: edge and outline of the image 421
11.1 edge detection 421
The basic concept of 11.1.1 edge detection 421
11.1.2 conventional edge detection 423
11.1.3 with direction edge detection 427
11.1.4 Laplasse operator 432
11.2 Hough transform 438
Conversion of 11.2.1 plane coordinate system 438
The idea of Hough 11.2.2 transform 440
11.2.3 straight line Hough transform 441
11.2.4 circle Hough transform 444
11.2.5 color image of the Hough transform 445
11.3 seed algorithm 448
11.3.1 algorithm introduced 448
11.3.2 programming 451
11.4 contour tracking 454
11.4.1 region representation method 454
The area and perimeter of the 11.4.2 calculation area 462
11.4.3 single area tracking 464
11.4.4 multi area tracking 467
11.5 image segmentation based on Morphological Watershed 469
11.5.1 basic concept 470
11.5.2 watershed algorithm 470
11.5.3 programming watershed segmentation 473
Twelfth chapter digital image encryption and hiding 478
12.1 chaos theory 478
The development of 12.1.1 chaos theory 478
The basic concept of 12.1.2 chaos 480
Measurement and determination of 12.1.3 chaos 482
12.2 examples of several typical chaotic systems 485
Logistic 12.2.1 mapping 485
Henon 12.2.2 mapping 488
Chebychev 12.2.3 mapping 488
12.3 chaotic encryption of digital images 489
12.3.1 cryptography and Chaos Cryptography 489
Classification of chaotic encryption algorithm based on 12.3.2 image 490
12.4 based on scrambling image encryption technology 491
12.4.1 digital image and permutation transform 491
12.4.2 using Hilbert curve scrambling image 492
12.4.3 Using Arnold transform scrambling image 495
Evaluation of digital image scrambling algorithm based on 12.4.4 499
12.5 chaos in the application of image encryption 499
12.5.1 based on the sorting method of chaos scrambling 500
12.5.2 based on the initial address method of chaos scrambling 507
12.5.3 chaotic encryption based on the gray value transform 507
Evaluation of chaotic encryption based on 12.5.4 510
12.6 digital image hiding technology 514
12.6.1 image fusion technology introduction 515
12.6.2 image hiding algorithm based on chaos 516
12.6.3 graphical user interface design 518
12.6.4 encoding to achieve 518
Wavelet transform and its application in the thirteenth Chapter 519
13.1 hall function and hall transform 519
13.1.1 the definition of the function of the hall 519
13.1.2 the nature of the function of the hall 520
13.1.3 unitary matrix and unitary transformation 521
13.1.4 two dimensional discrete linear transformation 521
13.1.5 Halki function 523
13.1.6 hall transform 525
13.2 the mathematical basis of wavelet 529
13.2.1 wavelet history 529
13.2.2 understand the concept of wavelet 530
13.2.3 multi resolution analysis 532
Construction of 13.2.4 wavelet function 536
13.2.5 wavelet series expansion 538
13.2.6 discrete wavelet transform 539
13.2.7 continuous wavelet transform 540
The admissibility conditions and basic characteristics of 13.2.8 wavelet 542
13.3 fast wavelet transform 543
13.3.1 fast wavelet transform 543
13.3.2 fast wavelet transform 547
13.3.3 image wavelet transform 549
13.4 application of wavelet in image processing 551
Fourteenth partial differential equations and image noise reduction 554
14.1 PM equation and its application 554
14.1.1 one dimensional heat conduction equation 554
14.1.2 anisotropic diffusion equation 559
Implementation of PM 14.1.3 diffusion equation 565
14.1.4 additive operator splitting 570
14.2 TV method and its application 578
14.2.1 functional and variational methods 578
14.2.2 total variation model 581
Numerical implementation of TV 14.2.3 algorithm 583
14.2.4 image denoising based on TV example 584

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    Focus on image processing, statistical analysis, data mining and machine learning. Welcome technical exchange! Language I prefer to use C/C++, Java, Prolog, Haskell, a small amount of Python and VB. Proficient in R and Matlab, slightly understand SPSS and Eviews. Please exchange blog, do not look for suggested (omega ^ ^)
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