DIP_PRACTICALS

        Digital  Image Processing
               Practical
Name: Anwesha Sanyal
Roll No: 3906


Practical-1(Reading and Displaying)

pkg load image;
I=imread("Panda.jpg");
imshow(I);

Practical-2 (Resize an image)
resizedI = imresize(I,0.25);
figure
imshow(resizedI)
Practical-3 (Gray scale image)
J = rgb2gray(I);
Figure
imshow(J);
Practical-4 (Black & White image)
figure imshow(im2bw(I));

Practical-5 (Color temperature of image)
r = size(I,1);
c = size(I,2);
R =zeros(r,c,3);
G = zeros(r,c,3);
B = zeros(r,c,3);
R( : , : ,1) = I( : , : ,1);
G( : , : ,2) = I( : , : ,2);
B( : , : ,3) = I( : , : ,3);
figure imshow(uint8(R));

figure imshow(uint8(G));

figure imshow(uint8(B));

Practical-6 (Negative of an image)
Image = imread(' Panda.jpg ');
J = rgb2gray(Image);
subplot(1,3,1);
imshow(J);
negativeImage = 255-J;   subplot(1,3,2); imshow(negativeImage);
for row=1:size(J,1)
for col=1:size(J,2)
negativeimage(row,col,:)=255-J(row,col,:); end
end
subplot(1,3,3); imshow(negativeimage);

Practical-7 (Stretching of an image)
subplot(1,2,1) imshow(Image);

J = imadjust(Image,stretchlim(Image),[]); subplot(1,2,2);
imshow(J);

Practical-8 (Applying filter on an image)
lap =[0,1,0;1,-4,1;0,1,0]; output=imfilter(I,lap); subplot(2,2,1);
imshow(output);
filteredImage = imadd(I,output); subplot(2,2,2); imshow(filteredImage);
l = [0,-1,0;-1,4,-1;0,-1,0]; output2=imfilter(I,l); subplot(2,2,3);
imshow(output2);

filteredImage2 = imadd(I,output2); subplot(2,2,4); imshow(filteredImage2);

Practical-9 (Prewitt Filter)
subplot(2,3,1);
imshow(I);
title('Original Image');

prewitt_H = [-1,-1,-1;0,0,0;1,1,1]; output_H = imfilter(I,prewitt_H); subplot(2,3,2); imshow(output_H);
title('prewitt_H');



filteredImage_H =imadd(I,output_H);
subplot(2,3,3); imshow(filteredImage_H); title('filteredImage_H');
prewitt_V = [-1,0,1;-1,0,1;-1,0,1]; output_V = imfilter(I,prewitt_V); subplot(2,3,4);
imshow(output_V);
title('prewitt_V');


filteredImage_V=imadd(I,output_V); subplot(2,3,5);
imshow(filteredImage_V); title('filteredImage_V');


filtered_img=imadd(I,output_H); filtered_image=imadd(filtered_img,output_V); subplot(2,3,6);
imshow(filtered_image);
title('prewitt');


Practical-10 (Zooming an image)
imshow(Image); title("zoomed image"); zoom(2);


Practical-11 (Translating an image)
pkg load image
i = imread(' Panda.jpg ');

subplot(1,2,1);
 imshow(i);
title("Original image");

set(gca, "Visible", "on"); j = imtranslate(i, [20,-40]); subplot(1,2,2); imshow(j);
title("translated Image");

set(gca, "Visible", "on");


Practical-12 (Shrinking an image)
f = input('Enter the shrinking factor: ');
s = size(A);
s1 = s/f;
k = 1;
l = 1;
for i=1:s1
for j=1:s1
B(i,j) = A(k,l); l = l+f;
end
l = 1;
k=k+f;
end

subplot(1,2,1); imshow(A);
title("Original image");

subplot(1,2,2); imshow(B); title("shrinkled image");



Practical-13 (Salt & pepper noise)
pkg load image
i=imread(' Panda.jpg ');
subplot(2,2,1);
imshow(i);
title('Original Image');
J = imnoise(i,'salt & pepper', 0.05);
subplot(2,2,2);
imshow(J);
title('Noisy Image');

##remove salt and pepper noise using averaging filter
H = fspecial('average',[3,3]);
Kaverage = imfilter(J,H);
subplot(2,2,3);
imshow(Kaverage);
title('Noise Free Image');

##remave salt and pepper noise usign median filter
i = rgb2gray(J);
Kmedian = medfilt2(i);
subplot(2,2,4);
imshow(Kmedian);
title('Noise free Image after median filter');





Practical-14 (Rotating an image)
j = imrotate(i, 90);
imshow(j);

Practical-15
subplot(1,3,1);
imshow(i);
title("Input image");

g = rgb2gray(i);
subplot(1,3,2);
imshow(g);
title("Gray Imgae");

f_transform = double(g);
f_transform1 = double(g);
h = fspecial('prewitt');
pre1 = uint8(round(filter2(h,g)));
subplot(1,3,3);
imshow(pre1);
         title("prewitt image");





Practical-16 (Laplacian filter)
subplot(1,3,1);
imshow(I);
title("original image");

lap = [0,1,0;1,-4,1;0,1,0];
output = imfilter(I,lap);



subplot(1,3,2);
imshow(output);
title("lap image");


filteredimage = imadd(I, output);
subplot(1,3,3);
imshow(filteredimage);
title("filtered image");





Practical-17 (Histogram equalisation)
imhist(i);
J = histeq(i); imhist(J); imshow(J);

Practical-18 (Erosion of image)
i = uint8(i); subplot(1,3,1); imshow(i);
i = im2bw(i); i= double(i); subplot(1,3,2); imshow(i);
se = [0,1,0;1,1,1;0,1,0]; se = strel("square", 3); erodedI = imerode(i, se); subplot(1,3,3); imshow(i);

Practical-19 (Edge detection of an image)
I=rgb2gray(i);
BW3 = edge(I,"roberts"); subplot(2,2,1); imshow(I);
title("original");

BW1 = edge (I,"prewitt"); subplot(2,2,2); imshow(BW1); title("prewitt");
BW2 = edge(I,"sobel"); subplot(2,2,3); imshow(BW2);
title("sobel");
BW3 = edge(I,"roberts"); subplot(2,2,4); imshow(BW3);
title("roberts");

Practical-20 (Dilation of image)
i = uint8(i);
subplot(2,2,1);
imshow(i);

i = im2bw(i);
i= double(i);
subplot(2,2,2);
imshow(i);

se = [0,1,0;1,1,1;0,1,0];
se = strel("square", 3);
erodedI = imerode(i, se);
subplot(2,2,3);
imshow(i);

dilateI = imdilate(erodedI, se);
subplot(2,2,4);
imshow(i);





Practical-21
pkg load image
sth=imread(' Panda.jpg');
r = size(sth,1);
c = size(sth,2);
sth = double(sth);
sum = 0;
for i = 1:r
   for j = 1:c
    sum = sum + sth(i,j,:);
   end
end
disp(sum)
disp(sum/(r*c))
J = imadjust(sth,stretchlim(sth),[]);
figure;
imshow(J);