image processing ideal LPF
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I made ideal LPF, but dont know it works well
Plz give me advice
close all;
I = rgb2gray(imread('testa.png'));
M = 512;
I = imresize(I, [M, M]);
[m, n] = size(I);
Ip = uint8(zeros(2*m, 2*n));
Ip(1:m,1:n) = double(I);
F = fft2(Ip);
D0 = round(M/10);
u = 0:2*M-1;
v = 0:2*M-1;
[u, v] = meshgrid(u,v);
D = sqrt( (u-((2*M+1)/2)).^2 + (v-((2*M+1)/2)).^2);
H = double(D <= D0);
G = H.*F;
g = ifft2(G);
subplot(2, 2, 1), imshow(I, []), title('Original Image');
subplot(2, 2, 2), imshow(log(1 + abs(fftshift(F))), []), title('Fourier Transform');
subplot(2, 2, 3), imshow(log(1 + abs((H))), []), title('Low-pass Filter');
subplot(2, 2, 4), imshow(real(g), []), title('Filtered Image');
Réponses (1)
There is no ideal LPF in general. Maybe there is for your particular image though depending on the high frequency noise in your image. To see how well your script/algorithm works, click the green run triangle. I'm attaching some of my demos for you to compare yours to.
Here's what yours does:
close all;
I = rgb2gray(imread('peppers.png'));
M = 512;
I = imresize(I, [M, M]);
[m, n] = size(I);
Ip = uint8(zeros(2*m, 2*n));
Ip(1:m,1:n) = double(I);
F = fft2(Ip);
D0 = round(M/10);
u = 0:2*M-1;
v = 0:2*M-1;
[u, v] = meshgrid(u,v);
D = sqrt( (u-((2*M+1)/2)).^2 + (v-((2*M+1)/2)).^2);
H = double(D <= D0);
G = H.*F;
g = ifft2(G);
subplot(2, 2, 1), imshow(I, []), title('Original Image');
subplot(2, 2, 2), imshow(log(1 + abs(fftshift(F))), []), title('Fourier Transform');
subplot(2, 2, 3), imshow(log(1 + abs((H))), []), title('Low-pass Filter');
subplot(2, 2, 4), imshow(real(g), []), title('Filtered Image');
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