Image Enhancement Technique in Frequency Filters using MATLAB with Source Code

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Image Enhancement Technique in Frequency Filter using MATLAB with Source Code

Digital Image Processing Using MATLAB

Enhancement in Frequency Domain Filtering

Spatial Domain

Frequency Domain

Major filter categories
Naturally, filters are categorized by examining their properties in the frequency domain:
Low-pass
High-pass
Band-pass
Band-stop

Example

Low-pass filters (Smoothing Filters):
Low-pass filters also known as called Smoothing Filters
Preserve low frequencies - useful for noise suppression

Example:

High-pass filters (Sharpening Filters)
High-pass filters also known as called Sharpening Filters
Preserves high frequencies - useful for edge detection

Example

Band-Stop filters

Frequency Domain Methods

Case 1:  h(u,v) is stated in the frequency domain.
Case 2:  h(x,y) is stated in the spatial domain.

Frequency domain filtering:

STEPS

F(u,v) = R(u,v) + jI(u,v)

G(u,v)= F(u,v)H(u,v) = H(u,v) R(u,v) + jH(u,v)I(u,v)

Types of Low Pass (LP) Filters
Ideal low-pass filter (ILPF)
Butterworth low-pass filter (BLPF)
Gaussian low-pass filter (GLPF)
Types of High Pass (LP) Filters
Ideal high-pass filter (IHPF)
Butterworth high-pass filter (BHPF)
Gaussian high-pass filter (GHPF)
Difference of Gaussians
Unsharp Masking and High Boost filtering

MATLAB Source Code For Image Enhancement in Frequency Filtering

%LOW PASS FILTER
clc;
clear all;
close all;
a=imread('coins.png');
[m,n]=size(a);
mask=zeros(m,n);
for i=150:180
    for j=210:240
        mask (i,j)=i;
    end
end
c=fftshift(mask);
b=fft2(a);
d=b.*c;
e=abs(ifft2(b));
figure(1);
subplot(3,3,1);
imshow(a);
title('original image');
subplot(3,3,2);
imshow(uint8(e));
title('low passs filtered image');
subplot(3,3,3);
imshow(mask);
subplot(3,3,4);
imshow(c);
title('mask after fftshift ooperation');
%HIGH PASS FILTER
a=imread('coins.png');
[m,n]=size(a);
mask=ones(m,n);
for i=150:180
    for j=210:240
        mask (i,j)=0;
    end
end
c=fftshift(mask);
b=fft2(a);
d=b.*c;
e=abs(ifft2(b));
subplot(3,3,5);
imshow(a);
title('original image');
subplot(3,3,6);
imshow(uint8(e));
title('high pass filtered image');
subplot(3,3,7);
imshow(mask);
subplot(3,3,8);
imshow(c);
title('high pass filter mask');
%BAND PASS  PASS FILTER
a=imread('coins.png');
[m,n]=size(a);
mask=zeros(m,n);
for i=160:170
    for j=260:230
        mask (i,j)=0;
    end
end
c=fftshift(mask);
b=fft2(a);
d=b.*c;
e=abs(ifft2(b));
figure(2);
subplot(2,2,1);
imshow(a);
title('original image');
subplot(2,2,2);
imshow(uint8(e));
title('band   pass filtered image');
subplot(2,2,3);
imshow(uint8(mask));
subplot(2,2,4);
imshow(uint8(c));
title('mask after fftshift ooperation');
% BAND REJECT FILTER
a=imread('coins.png');
[m,n]=size(a);
mask=ones(m,n);
for i=150:180
    for j=210:240
        mask(i,j)=0;
    end
end
c=fftshift(mask);
b=fft2(a);
d=b.*c;
e=abs(ifft2(b));
figure(3);
subplot(2,2,1);
imshow(a);
title('original image');
subplot(2,2,2);
imshow(uint8 (e));
title('band reject pass filtered image');
subplot(2,2,3);
imshow(mask);
subplot(2,2,4);
imshow(c);
title('high pass filter mask');

Result


Comments

  1. Justin1 September 2021 at 03:19

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