Question

Complete the MATLAB code - image convolution:

- Implement image convolution in Matlab:

-- Apply the following kernels and compare their images

-- If output is less than zero, set it to zero

-2 10 151 0 10 0 1 0 clear % Read image A-int32 (imread ( [N, M]-size (A) % change unsigned to signed integer for matrix computation %-define convolution kernel L= 1; % half size of kernel % initialize kernel data = zeros (2*1+1,2*1+1) ; 88%%%%%%%%%88%88% build kernel % cross-shaped kernel in here your %-convolution %-pad zeros to the original data Az-zeros (N+2*L,M+2*L) Y-zeros (size (A)) % initialize output image %%%%%%%%%%%%%%%%%%%%%%%%%%%% Put your own code for convolution here 옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹옹 uint8 (Y. *gt (Y, 0) /sum (surn (H) ) ) ; % normalize & neg Y ative value removal & convert to uint8 - %% Plot input, kernel & output figure (1) clf subplot (131) imshow (uint8 (A) ) title( 14 subplot (132) imshow (abs (H)) title( 14 subplot (133) imshow (Y) title( ,14 end of program

Answer 1

Below is matlab code:

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

close all,
clear all,
clc,

ProjectPath = pwd;
ImagePath = strcat(ProjectPath,'\Leena.jpg');
Orig = imread(ImagePath);
Gray = rgb2gray(Orig);
subplot(2,2,1); imshow(Gray); title('Original Gray Image');

%Convolution Filter-1
s = [0 1 0; 1 1 1; 0 1 0];
size(Gray)
A = uint8(conv2(Gray,s));
subplot(2,2,2); imshow(A); str= strcat(num2str(s)); title(str);

%Convolution Filter-1
s = [0 -1 0;-1 5 1;0 -1 0];
size(Gray)
A = uint8(conv2(Gray,s));
subplot(2,2,3); imshow(A); str= strcat(num2str(s)); title(str);

%Convolution Filter-1
s = [-2 -1 0;0 1 1;0 1 2];
size(Gray)
A = uint8(conv2(Gray,s));
subplot(2,2,4); imshow(A); str= strcat(num2str(s)); title(str);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

01 0 010 Original Gray Image 2-1 0 0 1 1 0 1 2 0-1 0 1 5 1 0-1 0