DIGITAL IMAGE PROCESSING 4th phần 7 doc

... x M y M x M 2 x M y M y M 2 = aA – u= bA – v= A – A T A[] 1– A= a i b i ,() jk,() 421 14 Digital Image Processing: PIKS Scientific Inside, Fourth Edition, by William K. Pratt Copyright © 20 07 by John Wiley & Sons, Inc. MORPHOLOGICAL IMAGE PROCESSING Morphological image processing ... priori expectation. 3 87 13 Digital Image Processing: PIKS Scientific Inside, Fourth...

Ngày tải lên: 14/08/2014, 02:20

... Exercises, 71 6 21.2 Image Manipulation Exercises, 71 7 21.3 Color Space Exercises, 71 8 21.4 Region-of-Interest Exercises, 72 0 21.5 Image Measurement Exercises, 72 1 21.6 Quantization Exercises, 72 2 21 .7 ... index. ISBN: 978 -0- 471 -76 777 -0 1. Image processing Digital techniques. I. Title. TA1632.P7 20 07 621.36&apos ;7 dc22 20060463 97 Printed in the United States of...

Ngày tải lên: 14/08/2014, 01:22

... quality. R ˜ N G ˜ N B ˜ N Y I Q 0.29889531 0.586622 47 0.11448223 0.595 977 99 0. 274 176 10– 0.32180189– 0.211 470 17 0.5226 171 1– 0.31114694 R ˜ N G ˜ N B ˜ N = R ˜ N G ˜ N B ˜ N 1.00000000 0.95608445 0.62088850 1.00000000 0. 271 376 64– 0.64860590– 1.00000000 ... 1.40168 676 1.00000000 0.34369538– 0 .71 416904– 1.00000000 1 .77 216042 0.00099022 Y Cb Cr = Y C 1 C 2 0.299 0.5 87 0.114...

Ngày tải lên: 14/08/2014, 01:22

... to (7. 4 -7) As a result of the separability of the selection operator, Eq. 7. 4 -7 reduces to (7. 4-8) Similarly, for Eq. 7. 4-6 describing sampled infinite-area superposition, (7. 4-9) Figure 7. 4-1 ... Lm 2 n 2 L+–,+()= ΔI B m 2 n 2 , B m 2 1 n 2 1+,+ = 1 47 6 Digital Image Processing: PIKS Scientific Inside, Fourth Edition, by William K. Pratt Copyright © 20 07 by John Wile...

Ngày tải lên: 14/08/2014, 02:20

... levels. H F c() H G d() 1 D⁄= PART 4 IMAGE IMPROVEMENT The use of digital processing techniques for image improvement has received much interest with the publicity given to applications in space imagery and medical research. ... source image to the gray scale of a destination image to best visualize certain details within the source image. Pardo and Sapiro (3) have proposed a dif...

Ngày tải lên: 14/08/2014, 02:20

... responses for the peppers_mon image. ( g ) Chebyshev 7 ( h ) Chebyshev 8 ( i ) Chebyshev 9 F ˆ ′′ rc,()2k 4 2 θsin 2k 5 θθcossin 2k 6 2 θcos++= 4k 7 θθcossin 2k 8 2 θcos+()r 2k 7 2 θsin 4k 8 θθcossin+()c++ 2k 9 2 θcos()r 2 8k 9 θθcossin()rc ... operators. FIGURE 15.5 -7 Edge gradient response as a function of edge displacement distance for sev- eral 7 × 7 orthogonal gradient oper...

Ngày tải lên: 14/08/2014, 02:20

... 2.48 2.31 5.62 4.05 1. 87 1 .72 Sand – raffia 15.26 15.08 13.22 12.98 3.85 3 .76 2 .74 2.49 6 .75 6.40 5.39 5.13 Sand – wool 19.14 19.08 17. 43 15 .72 14.43 14.38 12 .72 10.86 18 .75 12.3 10.52 8.29 Raffia ... – sand 9.80 9 .72 8.94 7. 48 6.39 6. 37 5.61 4.21 15.34 12.34 11.48 10.12 Grass – raffia 8. 47 8.34 6.56 4.66 10.61 10.49 8 .74 6.95 9.46 8.15 6.33 4.59 Grass – wool 4. 17 4.03 1....

Ngày tải lên: 14/08/2014, 02:20

... Research Report on Computer Processing of ERTS Images,” Report USCIPI 640, University of Southern California, Image Processing Institute, Los Angeles, September 1 975 . CONTINUOUS IMAGE SPATIAL FILTERING ... PQ= f ˆ Bf ˆ g= f ˆ gBfef{}+= ef{} f ˆ Wg= E M ef ˆ {}[] T ef ˆ {}[]gBf ˆ –[] T gBf ˆ –[]== f ˆ REFERENCES 305 49. W. Find, Image Coloration as an Interpretation Aid,” Proc. SPIE...

Ngày tải lên: 14/08/2014, 02:20

... 2,150. 47 2,215.32 2,344.02 1,080.29 1,101.21 1,153 .76 1,241.04 Rotated club 8 ,78 7 .71 4,363.23 4,220.96 2,196.08 2,103.88 2,0 57. 66 1,120.12 1,062.39 1,028.90 1,0 17. 60 Ellipse 8 ,72 1 .74 4,326.93 4, 377 .78 ... heart 34,523.13 17, 130.64 17, 442.91 8 ,76 2.68 8,658.34 9,402.25 4,608.05 4,442. 37 4,669.42 5,318.58 Minified heart 2,104. 97 1,0 47. 38 1,059.44 522.14 5 27. 16 535.38 2...

Ngày tải lên: 14/08/2014, 02:20

... feature is also useful in image processing. Example 7. 5 shows the sensitivity of this method for detect- ing small changes, even when they are in the higher derivatives. Example 7. 5 Construct a waveform ... (abs(fft(b,N))).v2; ps_unknown = (abs(fft(b_unknown,N))).v2; TLFeBOOK Advanced Signal Processing 2 27 F IGURE 8 .7 Configuration for adaptive noise cancellation. The reference c...

Ngày tải lên: 05/08/2014, 09:45