1.WAP to display the Negative of a digital Image
clear close all clc a= imread('lena.jpg'); b= im2double(a); c= 256*(1-b); d= uint8(c); subplot(2,1,1); imshow(a); title('original image'); subplot(2,1,2); imshow(d); title('negative image');
2.WAP to perform Thresholding on an input Image
clear all clc close all p= imread('pollen.tif'); a=p; [row col]= size(a); t= input('enter value of threshold:') for i= 1:1:row for j= 1:1:col if(p(i,j)< t) a(i,j)= 0; else a(i,j)= 255; end end end figure(1),imshow(p), title('original') figure(2),imshow(a),title('threshold')
3 WAP to perform gray level slicing without background
clear all clc p= imread('kidney.tif'); z= double(p); [row,col] = size(z) for i= 1:1:row for j= 1:1:col if((z(i,j)>150))&&(z(i,j)<250) z(i,j)= 255; else z(i,j)=0; end end end figure(1); imshow(p),title('original image') figure(2); imshow(uint8(z)),title('without background')
4. WAP to perform gray level slicing with background
clear all clc p= imread('kidney.tif'); z= double(p); [row,col] = size(z) for i= 1:1:row for j= 1:1:col if((z(i,j)>150))&&(z(i,j)<250) z(i,j)= 255; else z(i,j)=p(i,j);
end end end figure(1); imshow(p),title('original image') figure(2); imshow(uint8(z)),title('with background'
5. WAP to perform bit-plane slicing
clear all clc close all a = imread('pout.tif');
a= double(a); r = input('which bit image do u want to see. 1 = MSB 8 = LSB'); [row,col] = size(a); for x = 1:1:row for y = 1:1:col c= dec2bin(a(x,y),8); d= c(r); %w=double(d); w(x,y)= double(d);
if w(x,y)==49 %if double(d)==49 w(x,y)=255; else w(x,y)=0; end end end %figure(1) subplot(2,1,1) imshow(uint8(a)),title('original image') %figure(2) subplot(2,1,2) imshow(uint8(w)),title('bit-plane image')
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6. WAP to display Histogram of an image
clear all clc a= imread('lena.jpg'); a= double(a); [r,c]=size(a); h= zeros(1,300);
for n= 1:1:r for m= 1:1:c t= a(n,m); h(t) = h(t) + 1; end end %figure(1) subplot(2,1,1) imshow(uint8(a)),title('original Image') %figure(2) subplot(2,1,2) bar(h)
7.Prog for Ideal low pass filter
clear all clc close all a= imread('cameraman.tif'); a= double(a); c= size(a); N= c(1) D0= input('Enter the cut-off frequency'); for u=1:1:c(1) for v=1:1:c(2) D= (((u-N/2))^2+(v-(N/2))^2)^0.5;
if D
Ideal low pass filter
Do=180
8.Prog for Butterworth low pass
clear all clc close all a= imread('cameraman.tif'); a= double(a); c= size(a); N= c(1); n=input('Enter the order of filter'); D0=input('Enter the cut-off frequency'); for u= 1:1:c(1) for v= 1:1:c(2) D= (((u-(N/2))^2+(v-(N/2))^2))^0.5; H(u,v)=1/(1+((D/D0)^(2*n))); end end vv= fft2(a); vc=fftshift(vv); x= vc.*H; X= abs(ifft2(x)); figure(1),imshow(uint8(a)),title('original Image') figure(2),mesh(H),title('Butterworth Frequency Response') figure(3),imshow(uint8(X)),title('Filtered image') figure(4),imagesc(H),colormap(gray),TITLE('2D Butterworth Filter')
Butterworth low pass Filter
Order=2 Freq=15
9.Prog for Gaussian low pass
clear all clc close all a= imread('cameraman.tif'); a= double(a); c= size(a); N= c(1); %n=input('Enter the order of filter'); D0=input('Enter the cut-off frequency OR STANDARD DEVIATION'); for u= 1:1:c(1) for v= 1:1:c(2) Dx= (((u-(N/2))^2+(v-(N/2))^2))^0.5; D= Dx*Dx H(u,v)=exp(-D/(2*D0*D0)); end end vv= fft2(a); vc=fftshift(vv); x= vc.*H; X= abs(ifft2(x)); figure(1),imshow(uint8(a)),title('original Image') figure(2),mesh(H),title('GAUSSIAN Frequency Response') figure(3),imshow(uint8(X)),title('Filtered image') figure(4),imagesc(H),colormap(gray),TITLE('2D GAUSSIAN Filter')
Gaussian Low pass filter
10. Program for generating noise PDFs for Uniform, Rayleigh and Exponential Noise
clear all clc close all a=0;b=1; f = imread('testimage.tif'); f1=double(f); [r,c]= size(f); I= input('what type of noise? uniform=1,Rayleigh=2,Exp=3') if I==1 R= a+(b-a)*rand(r,c); elseif I==2 R= a+(-b*log(1-rand(r,c))).^0.5; elseif I==3 R=-log(1-rand(r,c)); end mmax = max(max(R)); mmin= min(min(R)); const = 100/(mmax-mmin); for x= 1:1:r for y= 1:1:c noise(x,y) = const*(R(x,y)-mmin); end end noisy_image = f1+noise; figure(1)
imshow(f),title('original Image') figure(2) hist(noise),title('noise PDF') figure(3) imshow(uint8(noisy_image)),title('Noisy Image')
