DIGITAL IMAGE PROCESSING 4th phần 2 docx

... Exercises, 723 21 .8 Unitary Transform Exercises, 724 21 .9 Linear Processing Exercises, 725 21 .10 Image Enhancement Exercises, 726 21 .11 Image Restoration Models Exercises, 728 21 . 12 Image Restoration ... a Kx 1 y 1 t 1 x 2 y 2 t 2 ,,;,,()EFx 1 y 1 t 1 ,,()η F x 1 y 1 t 1 ,,()–[]F ∗ x 2 y 2 t 2 ,,()η ∗ F x 2 y 2 t 2 ,,()–[]{}= Kx 1 y 1 t 1 x 2 y 2 t 2...

Ngày tải lên: 14/08/2014, 01:22

... 9. ( b ) 11 21 31 0 0 11 21 31 31 0 11 21 21 31 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 23 33 0 0 13 23 33 33 0 13 23 23 33 0 13 12 22 32 0 0 12 22 32 32 0 12 22 22 32 0 12 12 22 32 0 0 12 22 32 32 0 12 22 22 32 0 12 11 21 31 0 0 11 21 31 31 0 11 21 21 31 0 11 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 23 33 0 0 13 23 33 33 0 13 23 23 33 0 13...

Ngày tải lên: 14/08/2014, 02:20

... definition. H uv,()G uv,()=0uN2⁄≤≤ 0 vN2⁄≤≤ 0 uN2⁄≤≤ 1 N 2 + vN1–≤≤ 1 N 2 + uN1–≤≤ 0 vN2⁄≤≤ 1 N 2 + uN1–≤≤ 1 N 2 + vN1–≤≤ G uv,() 1 2 – s u u() 2 s v v() 2 +[] ⎩⎭ ⎨⎬ ⎧⎫ exp= 22 4 LINEAR PROCESSING TECHNIQUES Then, ... C++,++() ∑∑ = Gjk,() L 1–( )2 33× H 1 9 111 111 111 = H 1 10 111 121 111 = H 1 16 121 24 2 121 = 33× H 1 b 2+ ⎝⎠ ⎛⎞ 2 1 b 1 bb 2 b 1 b 1 = FAST...

Ngày tải lên: 14/08/2014, 02:20

... gxs,()gys,(){}∇ 2 –= Hxy,() 1 πs 4 1 x 2 y 2 + 2s 2 – ⎝⎠ ⎜⎟ ⎛⎞ x 2 y 2 + 2s 2 – ⎩⎭ ⎨⎬ ⎧⎫ exp= 474 EDGE DETECTION and in square-root form as (15 .2- 6b) where (15 .2- 6c) (15 .2- 6d) The edge orientation ... 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 2k 9 2 θsin()c...

Ngày tải lên: 14/08/2014, 02:20

... 4.59 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 ... 3.78 Average 5 .21 3.55 2. 30 a 1: S (2, 0), S(0, 2) , S(1, 1), S (2, 2). b 2: S(1,1), S (2, 2). c 3: S (2, 2). O · {} Wjk,() A F mn,() H W jk,() W ˆ jk,()Fjk,()H...

Ngày tải lên: 14/08/2014, 02:20

... revision, (3.4-5) T ˜ 1 C() T 1 C() T 1 P ˜ 2 ()T 1 P ˜ 3 () T 2 C() T 2 P ˜ 2 ()T 2 P ˜ 3 () T 3 C() T 3 P ˜ 2 ()T 3 P ˜ 3 () T 1 W ˜ ()T 1 P ˜ 2 ()T 1 P ˜ 3 () T 2 W ˜ ()T 2 P ˜ 2 ()T 2 P ˜ 3 () T 3 W ˜ () T 3 P ˜ 2 () T 3 P ˜ 3 () ... = T ˜ 3 C() T 1 P ˜ 1 ()T 1 P ˜ 2 ()T 1 C() T 2 P ˜ 1 ()T 2 P ˜ 2 ()T 2 C() T 3 P ˜ 1 ()T 3 P ˜ 2 ()T 3 C() T 1 P ˜ 1 ()...

Ngày tải lên: 14/08/2014, 01:22

... equation (11 .2- 9) FIGURE 11 .2- 2. Cross section of transfer function of a lens. Numbers indicate degree of misfocus. Hxy,()K 1 K 2 x 2 K 3 y 2 +() 56⁄ – ⎩⎭ ⎨⎬ ⎧⎫ exp= Hxy,()K x 2 2b x 2 y 2 2b y 2 + ⎝⎠ ⎜⎟ ⎛⎞ – ⎩⎭ ⎨⎬ ⎧⎫ exp= F O i() xyt j ,,()O C C ... RESTORATION 341 If the ideal image and observed image means are nonzero, the proper form of the reconstructed image Fo...

Ngày tải lên: 14/08/2014, 02:20

... mM≤≤() x m y m ,() u T u 1 u 2 … u M ,,,[]= v T v 1 v 2 … v M ,,,[]= a T a 0 a 1 … a 5 ,,,[]= b T b 0 b 1 … b 5 ,,,[]= E uAa–() T uAa–()vAb–() T vAb–()+= A 1 x 1 y 1 x 1 2 x 1 y 1 y 1 2 1 x 2 y 2 x 2 2 x 2 y 2 y 2 2 1 ... Multichannel Images,” IEEE Trans. Signal Processing, 39, 10, October 1991, 22 22 22 36. 66. H. Altunbasak and H. J. Trussell, “Colorimetric Restoration...

Ngày tải lên: 14/08/2014, 02:20

... radians. λ 1 1 2 U 20 ,()U 02, ()+[] 1 2 U 20 ,() 2 U 02, () 2 2U 20 ,()U 02, ()4U 11,() 2 +–+[] 12 += λ 2 1 2 U 20 ,()U 02, ()+[] 1 2 U 20 ,() 2 U 02, () 2 2U 20 ,()U 02, ()4U 11,() 2 +–+[] 12 –= λ M MAX ... 5,318.58 Minified heart 2, 104.97 1,047.38 1,059.44 522 .14 527 .16 535.38 26 0.78 26 2. 82 266.41 27 1.61 Diamond 8,561. 82 4,349.00 4,704.71...

Ngày tải lên: 14/08/2014, 02:20

... quantization step size, δ=V MAX /2 N . Assuming that the error is uniformly distributed between −δ /2 +δ /2, the variance, σ,is: σ= ∫ δ /2 −δ /2 η 2 /δ dη=V 2 Max (2 −2N )/ 12 (8) Assuming a uniform distribution, ... box and record the following output: Frequency (Hz): 2 10 20 60 100 125 150 20 0 300 400 V out volts rms: .15×10 −7 0.1×10 −3 0.0 02 0 .2 1.5 3 .28 4.47 4.97 4....

Ngày tải lên: 23/07/2014, 19:20