Image Enhancement Frequency Domain

clc;clear all;close all;
im=imread(‘car.jpg’);
im1=rgb2gray(im);                   % RGB2GRAY –> Convert RGB image or colormap to grayscale.
im2=medfilt2(im1,[3 3]);            % MEDFILT2 –> Perform 2-D median filtering. Median filtering the image to remove noise

BW = edge(im2,’sobel’);             % EDGE –> Find edges in intensity image.
[imx,imy]=size(BW);                  % Dimensions

msk=[0 0 0 0 0;                      % Mask
     0 1 1 1 0;
     0 1 1 1 0;
     0 1 1 1 0;
     0 0 0 0 0;];

B=conv2(BW,msk);                    % CONV2 Two dimensional convolution. Smoothing image
      % to reduce the number of connected components

L = bwlabel(B,8); % BWLABEL-> Calculating connected components
mx=max(max(L));
[r,c] = find(L==15); % FIND-> Find indices of nonzero elements.
rc = [r c];

[sx sy]=size(rc);
n1=zeros(imx,imy);                  % zeros –> Zeros array

for i=1:sx
    x1=rc(i,1);
    y1=rc(i,2);
    n1(x1,y1)=255;                  % Storing the extracted image in an array
end                                

figure(‘Name’,’Input Image’),imshow(im);
figure(‘Name’,’Gray Image’),imshow(im1);
figure(‘Name’,’Median Filtered Image (Noise Removal)’),imshow(im2);
figure(‘Name’,’Smoothing Image’),imshow(B);
figure(‘Name’,’Extracted Image’),imshow(n1,[]);

I = imread(‘canoe.tif’);
BW1 = edge(I,’sobel’);
BW2 = edge(I,’canny’);
figure, imshow(I)
figure, imshow(BW1)
figure, imshow(BW2)