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Practical 1
# 2D Linear Convolution, Circular Convolution between two 2D matrices
clear all;
close;
clc;
//h=[1,2,3,3,2,1];
//x=[1,2,3,4,5];
h=[[1,2,3],[4,5,6],[7,8,9]];
x=[[1,2,3],[4,5,6],[7,8,9]];
//x=input('Enter the i/p seq');
//h=input('Enter the i/p seq');
y=convol(x,h);
for i=1;length(y)
if(y(i)<=0.0001)
y(i)=0;
end
end
disp(y,'linear convolution of y')
subplot(3,1,2)
a=gca();
a.thickness=2;
plot2d3('gnn',[0:length(h)-1],h)
xtitle('impulse response','n','h[n]');
subplot(3,1,1);
a=gca();
a.thickness=2;
plot2d3('gnn',[0:length(x)-1],x)
xtitle('impulse response','n','x[n]');
subplot(3,1,3);
a=gca();
a.thickness=2;
plot2d3('gnn',[0:length(y)-1],y)
xtitle('impulse response','n','y[n]');
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Practical 2
# Circular Convolution expressed as linear convolution plus alias
clear all;
close;
clc;
h=[1,2,3,3,2,1];
x=[1,2,3,4,5,6];
//h=[[1,2,3],[4,5,6],[7,8,9]];
//x=[[1,2,3],[4,5,6],[7,8,9]];
//x=input('Enter the i/p seq');
//h=input('Enter the i/p seq');
m=length(h);
n=length(x);
a=zeros(1,max(m,n))
if(m>n)
for i=n+1;m
h(i)=0;
end
else if(n>m)
for i=m+1;n
x(i)=0;
end
end
//n=length(x);
y=zeros(1,n);
a(1)=x(1);
for j = 2:n
a(j) = x(n-j +2) ;
end
for i =1: n
y (1) = y (1) +h(i)*a(i);
end
for k = 2:n
for j =2: n
x(j) = a(j -1) ;
end
x (1) = a(n);
x
for i = 1:n
a(i) = x(i);
y(k) = y(k)+h(i)*a(i);
end
end
disp(y ,'Circular convolution' )
end
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Practical 3
# Linear Cross correlation of a 2D matrix, Circular correlation between two
signals and Linear auto correlation of a 2D matrix, Linear Cross correlation of a
2D matrix
clear;
clc;
close;
h=[1,2,3,0]; //Impulse Response of LTI System
x=[1,2,2,1]; //Input Response of LTI System
N1=length(x);
N2=length(h);
N=N1+N2-1
disp(N,'Length of Output Response y (n)')
//Padding zeros to Make Length of h and x
//Equal to length of output response y
h1=[h,zeros(1,N-N2)];
x1=[x,zeros(1,N-N1)];
//Computing FFT
H=fft(h1, -1) ;
X=fft(x1, -1) ;
//Multiplication of 2 DFTs
Y=X.*H
//Linear Convolution Result
y=abs(fft(Y,1))
disp(X,'DFT of i/p X(k)=')
disp(H,'DFT of impulse sequence H(k)=')
disp(Y,'DFT of Linear Filter o/p Y(k)=')
disp(y,'Linear Convolution result y [n]=')
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Practical 4

# DFT of 4x4 gray scale image

clear all;
clc;
x=[1 2 3 4; 1 0 1 4; 1 1 0 1; 1 0 1 0];
p=[1 1 1 1; 1 -%i -1 %i; 1 -1 1 -1; 1 %i -1 -%i];
y=x*p;
disp(y)
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Practical 5
#Compute discrete cosine transform
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# Program to perform KL transform for the given 2D matrix

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Practical 6

# Brightness enhancement of an image, Contrast Manipulation, image

negative

 Contrast Manipulation(Stretching)
clc;
aa=imread('Picture1.jpg');
a=double(aa)
[row col]=size(a)
LT=input('Enter lower threashold value')
UT=input('Enter upper threashold value')
for x=1:1:row
for y=1:1:col
if a(x,y)<=LT
b(x,y)=0.5*a(x,y)
else if a(x,y)<=UT
b(x,y)=2*(a(x,y)-LT)+0.5*LT;
else b(x,y)=0.5*(a(x,y)-UT)+0.5*LT+2*(UT-LT);
end
end
end
end
subplot(2,1,1)
imshow(a)
title('Original image')
subplot(2,1,2)
imshow(b)
title('Image after Constrast Stretching')
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 image negative( DigitalNegative)

clc;
aa=imread('Picture1.jpg');
a=double(aa)
c=max(max(a))
b=c-a
figure(1)
//4colormap(gray)
imshow(a)
figure(2)
//colormap(gray)
imshow(b)
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Practical 7
# Perform threshold operation, perform gray level slicing without background

 thresholding
clc;
p=imread('Picture1.jpg');
a=p
[row col]=size(a)
T=input('Enter threashold value')
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),figure(2),imshow(a)
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 gray level slicing without background

clc;
p=imread('Picture1.jpg');
a=p
[row col]=size(a)
for i=1:1:row
for j=1:1:col
if (a(i,j)>50 & a(i,j)<150)
a(i,j)=255;
else
a(i,j)=0;
end
end
end
figure(1),imshow(p),figure(2),imshow(a)
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Practical 8
Image Segmentation
 OrdinaryOperator.sce
clc;
aa=imread('Picture1.jpg');
a=double(aa)
[row col]=size(a)
y=zeros(a)
w1=[1 0; -1 0]
w2=[1 -1; 0 0]
for x=2:1:row-1
for y=2:1:col-1
a1(x,y)=[w1(1)*a(x,y)+w1(2)*a(x,y+1)+w1(3)*a(x+1,y)+w1(4)*a(x+1,y+1)];
a2(x,y)=[w2(1)*a(x,y)+w2(2)*a(x,y+1)+w2(3)*a(x+1,y)+w2(4)*a(x+1,y+1)];
end
end
a3=a1+a2
figure(1),imshow(a1),figure(2),imshow(a2),figure(3),imshow(a3)

 PrewittsOperation
clc;
aa=imread('Picture1.jpg');
a=double(aa)
[row col]=size(a)
w1=[-1 -1 -1; 0 0 0; 1 1 1]
w2=[-1 0 1; -1 0 1; -1 0 1]
for x=2:1:row-1
for y=2:1:col-1
a1(x,y)=[w1(1)*a(x-1,y-1)+w1(2)*a(x-1,y)+w1(3)*a(x-1,y+1)+w1(4)*a(x,y-
1)+w1(5)*a(x,y)+w1(6)*a(x,y+1)+w1(7)*a(x+1,y-1)+w1(8)*a(x+1,y)+w1(9)*a(x+1,y+1)];
a2(x,y)=[w2(1)*a(x-1,y-1)+w2(2)*a(x-1,y)+w2(3)*a(x-1,y+1)+w2(4)*a(x,y-
1)+w2(5)*a(x,y)+w2(6)*a(x,y+1)+w2(7)*a(x+1,y-1)+w2(8)*a(x+1,y)+w2(9)*a(x+1,y+1)];
end
end
a3=a1+a2
figure(1),imshow(a1),figure(2),imshow(a2),figure(3),imshow(a3)
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 RobertsOperator
clc;
aa=imread('Picture1.jpg');
a=double(aa)
[row col]=size(a)
w1=[1 0; 0 -1]
w2=[0 1; -1 0]
for x=2:1:row-1
for y=2:1:col-1
a1(x,y)=[w1(1)*a(x,y)+w1(2)*a(x,y+1)+w1(3)*a(x+1,y)+w1(4)*a(x+1,y+1)];
a2(x,y)=[w2(1)*a(x,y)+w2(2)*a(x,y+1)+w2(3)*a(x+1,y)+w2(4)*a(x+1,y+1)];
end
end
a3=a1+a2
figure(1),imshow(a1),figure(2),imshow(a2),figure(3),imshow(a3)

 SobelOperator.sce
clc;
aa=imread('Picture1.jpg');
a=double(aa)
[row col]=size(a)
w1=[-1 -2 -1; 0 0 0; 1 2 1]
w2=[-1 0 1; -2 0 2; -1 0 1]
for x=2:1:row-1
for y=2:1:col-1
a1(x,y)=[w1(1)*a(x-1,y-1)+w1(2)*a(x-1,y)+w1(3)*a(x-1,y+1)+w1(4)*a(x,y-
1)+w1(5)*a(x,y)+w1(6)*a(x,y+1)+w1(7)*a(x+1,y-1)+w1(8)*a(x+1,y)+w1(9)*a(x+1,y+1)];
a2(x,y)=[w2(1)*a(x-1,y-1)+w2(2)*a(x-1,y)+w2(3)*a(x-1,y+1)+w2(4)*a(x,y-
1)+w2(5)*a(x,y)+w2(6)*a(x,y+1)+w2(7)*a(x+1,y-1)+w2(8)*a(x+1,y)+w2(9)*a(x+1,y+1)];
end
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end
a3=a1+a2
figure(1),imshow(a1),figure(2),imshow(a2),figure(3),imshow(a3)
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Practical 9
# Image Compression
close ;
clear ;
clc ;
x =[65 ,75 ,80 ,70;72 ,75 ,82 ,68;84 ,72 ,62 ,65;66 ,68 ,72 ,80];
disp (x , 'Original Block is x = ' )
[ m1 n1 ]= size ( x ) ;
blk = input ( 'Enter the block size : ') ;
for i = 1 : blk : m1
for j = 1 : blk : n1
y = x ( i: i +(blk-1) ,j : j +(blk-1) ) ;
m = mean ( mean ( y ) ) ;
disp (m , 'mean value is m = ' )
sig = stdev (y ) ;
disp ( sig , 'Standard deviation of the block is= ' )
b = y > m ; // the binary block
disp (b , 'Binary allocation matrix is B= ')
K = sum (sum ( b ) ) ;
disp (K , 'number of ones = ')
if ( K ~= blk ^2 ) & ( K ~= 0)
ml = m - sig * sqrt ( K /(( blk ^2) -K ) ) ;
disp ( ml , ' The value of a = ')
mu = m+ sig * sqrt ((( blk ^2) -K )/ K ) ;
disp ( mu , 'The value of b = ')
x ( i : i +( blk -1) , j : j +( blk -1) ) = b * mu+(1 - b ) * ml ;
end
end
end
disp ( round ( x ) , 'Reconstructed Block is x = ')
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Practical 10
#Binary Image Processing and Colour Image processing
 BoundryExtraction

clc;
aa=imread('Picture1.jpg');
aa=double(aa)
p=size(aa)
da=aa
ea=aa
w1=[1 1 1; 1 1 1; 1 1 1]
for x=2:1:p(1)-100
for y=2:1:p(2)-100
a1=[w1(1)*a(x-1,y-1) w1(2)*a(x-1,y) w1(3)*a(x-1,y+1) w1(4)*a(x,y-1) w1(5)*a(x,y) w1(6)*a(x,y+1)
w1(7)*a(x+1,y-1) w1(8)*a(x+1,y) w1(9)*a(x+1,y+1)];
A(x,y)=min(a1) //Erosion
sharp(x,y)=double(a(x,y))-double(A(x,y))
end
end
figure(1),imshow(aa)
figure(2),imshow(A)
figure(3),imshow(sharp)

 Opening

clc;
aa=imread('Picture1.jpg');
aa=double(aa)
p=size(aa)
a=aa
w1=[1 1 1; 1 1 1; 1 1 1]
for x=2:1:p(1)-100
for y=2:1:p(2)-100
a1=[w1(1)*a(x-1,y-1) w1(2)*a(x-1,y) w1(3)*a(x-1,y+1) w1(4)*a(x,y-1) w1(5)*a(x,y) w1(6)*a(x,y+1)
w1(7)*a(x+1,y-1) w1(8)*a(x+1,y) w1(9)*a(x+1,y+1)];
A1(x,y)=min(a1) //Erosion
a=A1
end
end
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q=size(a)
for i=2:1:q(1)-100
for j=2:1:q(2)-100
a11=[w1(1)*A1(i-1,j-1) w1(2)*A1(i-1,j) w1(3)*A1(i-1,j+1) w1(4)*A1(i,j-1) w1(5)*A1(i,j)
w1(6)*A1(i,j+1) w1(7)*A1(i+1,j-1) w1(8)*A1(i+1,j) w1(9)*A1(i+1,j+1)];
A2(i,j)=max(a11) //Dilation
end
end
figure(1),imshow(a)
figure(2),imshow(A2)

 Colorimagerocessing

clc ;
close ;
RGB = imread ('Picture1.jpg') ;
R = RGB ;
G = RGB ;
B = RGB ;
R (: ,: ,2) =0;
R (: ,: ,3) =0;
G (: ,: ,1) =0;
G (: ,: ,3) =0;
B (: ,: ,1) =0;
B (: ,: ,2) =0;
figure (1)
imshow ( RGB ) ; //IPD
//t o o l b o x
title ('Original Color Image') ;
figure (2)
imshow (R) ;
figure (3)
imshow (G) ;
figure (4)
imshow (B) ;
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 Closing

clc;
aa=imread('Picture1.jpg');
aa=rgb2gray(aa)
aa=double(aa)
p=size(aa)
da=aa
ea=aa
w1=[1 1 1; 1 1 1; 1 1 1]
for x=2:1:p(1)-100
for y=2:1:p(2)-100
a1=[w1(1)*a(x-1,y-1) w1(2)*a(x-1,y) w1(3)*a(x-1,y+1) w1(4)*a(x,y-1) w1(5)*a(x,y) w1(6)*a(x,y+1)
w1(7)*a(x+1,y-1) w1(8)*a(x+1,y) w1(9)*a(x+1,y+1)];
A1(x,y)=max(a1) //Dilation
da=A1
end
end
q=size(da)
for i=2:1:q(1)-100
for j=2:1:q(2)-100
a11=[w1(1)*A1(i-1,j-1) w1(2)*A1(i-1,j) w1(3)*A1(i-1,j+1) w1(4)*A1(i,j-1) w1(5)*A1(i,j)
w1(6)*A1(i,j+1) w1(7)*A1(i+1,j-1) w1(8)*A1(i+1,j) w1(9)*A1(i+1,j+1)];
A2(i,j)=min(a11) //Erosion
ea=A2
end
end
figure(1),imshow(aa)
figure(2),imshow(ea)