图像处理报告 第五章所有报告 冈萨雷斯 全英文 原创 Digital Image Processing.doc

Digital Image Processing Project chapter Chapter 5 Project number Proj05 01 Proj05 04 Student s name Student s number Class 1 Contents NOISE GENERATORS 2 NOISE REDUCTION USING A MEDIAN FILTER 2 PERIODIC NOISE REDUCTION US ING A NOTCH FILTER 4 PARAMETRIC WIENER FILTER 7 2 Noise Generators Exp 16 PROJECT 05 01 Multiple Uses Objective To know how to generate noise images with different probability density functions distributions The noise im ages are useful in simulation for image enhancement and image restoration Requirements This is a generic project in the sense that the programs developed here are used in several of the projects that follow See Fig 5 2 for the shapes and parameters of the following noise probability density functions a Find or develop a program to add Gaussian noise to an image You must be able to sp ecify the noise mean and variance b Find or develop a program to add salt and pepper impulse noise to an image You must be able to specify the probabilities of each of the two noise components Figure 1 Fig5 03 jpg 1 Program listings I imread Fig5 03 jpg r imnoise I gaussian 0 0 01 m 5000 subplot 2 2 1 imshow r title original subplot 2 2 2 imhist r m title gaussian r1 imnoise I salt m 100 subplot 2 2 3 imshow r1 title add noise subplot 2 2 4 imhist r1 m title salt Discussion of results original 0 200 400 gaussian 0100200 add noise 0 2000 4000 6000 8000 salt figure 1 subplot 211 imshow f title original g imnoise f salt subplot 223 imshow g title salt f1 medfilt2 g 3 3 symmetric subplot 224 imshow f1 title median filter Discussion of results original salt C 343 0 r R S imnoise3 688 688 C 40000000 subplot 221 imshow r title noise I1 double I I2 r I1 subplot 222 I3 uint8 I2 imshow I3 title add noise M N size I I1 double I3 F fft2 I subplot 223 imshow F title fourier frequency sig 100 H lpfilter gaussian M N sig G H F g real ifft2 G I4 uint8 g subplot 224 imshow I4 title after LPF 6 Discussion of results noiseadd noise fourier frequencyafter LPF Figure 6 results of project 05 03 7 Parametric Wiener Filter Exp 19 PROJECT 05 04 Objective To understand the high performance of the parametric Wiener Filter in image restoration when there are additive noise after the image degradation Requirements a Implement a blurring filter as in Eq 5 6 11 b Blur image 5 26 a in the 45 direction using T 1 as in Fig 5 26 b c Add Gaussian noise of 0 mean an d variance of 10 pixels to the blurred image d Restore the image using the parame tric Wiener filter given in Eq 5 8 3 Figure 7 Fig5 26 a jpg 8 Program listings f imread Fig5 26 a jpg I im2double f figure 1 subplot 221 imshow f title original PSF fspecial motion 21 45 gb imfilter f PSF conv circular subplot 222 imshow gb title circular convolution noise var 0 0001 noise imnoise gb gaussian 0 noise var subplot 234 imshow noise title blurred and noise fr1 deconvwnr noise PSF 0 subplot 235 imshow fr1 title simple Wiener estimated nsr noise var var I fr2 deconvwnr noise PSF estimated nsr subplot 236 imshow fr2 title constant ratio W