如果您查看图像的fft,您可以清楚地看到导致图像中图案的强频率.
您需要创建一个陷波滤波器,将这些高峰周围的区域归零.我尝试使用高斯陷波滤波器进行此操作,得到的频谱看起来像这样.
ifft图像(对比度增强)证明是
这是用于构建和应用过滤器的一些MATLAB代码
I = imread('YmW3f.png');
ft = fftshift(fft2(I));
[m,n] = size(ft);
% define some functions
norm_img = @(img) (img - min(img(:))) / (max(img(:)) - min(img(:)));
show_spec = @(img) imshow(norm_img(log(abs(img)-min(abs(img(:)))+1.0001)));
gNotch = @(v,mu,cov) 1-exp(-0.5*sum((bsxfun(@minus,v,mu).*(cov\bsxfun(@minus,v,mu)))));
% show spectrum before
figure();
show_spec(ft);
% by inspection
cx = 129;
cy = 129;
% distance of noise from center
wx1 = 149.5-129;
wx2 = 165.5-129;
wy = 157.5-129;
% create notch filter
filt = ones(m,n);
% use gaussian notch with standard deviation of 5
sigma = 5;
[y,x] = meshgrid(1:n, 1:m);
X = [y(:) x(:)].';
filt = filt .* reshape(gNotch(X,[cx+wx1;cy+wy],eye(2)*sigma^2),[m,n]);
filt = filt .* reshape(gNotch(X,[cx+wx2;cy+wy],eye(2)*sigma^2),[m,n]);
filt = filt .* reshape(gNotch(X,[cx-wx1;cy-wy],eye(2)*sigma^2),[m,n]);
filt = filt .* reshape(gNotch(X,[cx-wx2;cy-wy],eye(2)*sigma^2),[m,n]);
% apply filter
ft = ft .* filt;
% show spectrum after
figure();
show_spec(ft);
% compute inverse
ifft_ = ifft2(ifftshift( ft));
img_res = histeq(norm_img(ifft_));
figure();
imshow(img_res);
编辑：由于Todd Gillette指示的原因,为meshgrid交换了参数.
如果觉得《matlab中陷波滤波器消除 matlab – 找到合适的陷波滤波器以从图像中移除图案》对你有帮助，请点赞、收藏，并留下你的观点哦！
