从this answer开始,我知道如何创建高通巴特沃斯滤波器。
来自this video,我知道, lowpasskernel = 1 - highpasskernel
。
所以,我创建了以下低通巴特沃斯滤波器,
function [out, kernel] = butterworth_lp(I, Dl, n)
height = size(I, 1);
width = size(I, 2);
[u, v] = meshgrid(-floor(width/2):floor(width/2)-1,-floor(height/2):floor(height/2)-1);
% lp_kernel = 1 - hp_kernel
kernel = 1 - butter_hp_kernel(u, v, Dl, n);
% fft the image
I_fft_shifted = fftshift(fft2(double(I)));
% apply lowpass filter
I_fft_shift_filtered = I_fft_shifted .* kernel;
% inverse FFT, get real components
out = real(ifft2(ifftshift(I_fft_shift_filtered)));
% normalize and cast
out = (out - min(out(:))) / (max(out(:)) - min(out(:)));
out = uint8(255*out);
function k = butter_hp_kernel(u, v, Dh, n)
uv = u.^2+v.^2;
D = sqrt(uv);
frac = Dh./D;
p = 2*n;
denom = frac.^p;
k = 1./denom;
输出
这不是低通滤波器输出。
那么,我的代码有什么问题?
答案 0 :(得分:2)
您没有在高通滤镜中正确复制公式:
uv = u.^2+v.^2;
D = uv.^0.5;
frac = Dh./D;
p = 2*n;
denom = frac.^p;
k = 1./(1+denom); --> you forgot the "1+"
新输出:
答案 1 :(得分:-1)
好。我按照following formula (Page #8/48),
解决了这个问题输出
源代码
<强> butter_lp_kernel.m 强>
function f = butter_lp_f(u, v, Dl, n)
uv = u.^2+v.^2;
Duv = sqrt(uv);
frac = Duv./Dl;
denom = frac.^(2*n);
f = 1./(1.+denom);
function k = butter_lp_kernel(I, Dl, n)
Height = size(I,1);
Width = size(I,2);
[u, v] = meshgrid( ...
-floor(Width/2) :floor(Width-1)/2, ...
-floor(Height/2): floor(Height-1)/2 ...
);
k = butter_lp_f(u, v, Dl, n);
<强> ifftshow.m 强>
function out = ifftshow(f)
f1 = abs(f);
fm = max(f1(:));
out = f1/fm;
end
<强> butterworth_lpf.m 强>
function [out1, out2] = butterworth_lpf(I, Dl, n)
Kernel = butter_lp_kernel(I, Dl, n);
I_ffted_shifted = fftshift(fft2(I));
I_ffted_shifted_filtered = I_ffted_shifted.*Kernel;
out1 = ifftshow(ifft2(I_ffted_shifted_filtered));
out2 = ifft2(ifftshift(I_ffted_shifted_filtered));
end