双边滤波与一般的高斯滤波的不同就是:双边滤波既利用了位置信息<or 几何信息——高斯滤波只用了位置信息>又利用了像素信息来定义滤波窗口的权重。
像素值越接近,权重越大。双边滤波会去除图像的细节信息,又能保持边界。
对于彩色图像,像素值的接近与否不能使用RGB空间值,双边滤波的原始文献建议使用CIE颜色空间。
代码如下:
function resultI = BilateralFilt2(I,d,sigma)
%%%
%Author:LiFeiteng
%Version:1.0——灰色图像 Time:2013/05/01
%Version:1.1——灰色/彩色图像 Time:2013/05/02 2013/05/05
%d 半窗口宽度
I = double(I);
if size(I,3)==1
resultI = BilateralFiltGray(I,d,sigma);
elseif size(I,3)==3
resultI = BilateralFiltColor(I,d,sigma);
else
error('Incorrect image size')
end
end
function resultI = BilateralFiltGray(I,d,sigma)
[m n] = size(I);
newI = ReflectEdge(I,d);
resultI = zeros(m,n);
width = 2*d+1;
%Distance
D = fspecial('gaussian',[width,width],sigma(1));
S = zeros(width,width);%pix Similarity
h = waitbar(0,'Applying bilateral filter...');
set(h,'Name','Bilateral Filter Progress');
for i=1+d:m+d
for j=1+d:n+d
pixValue = newI(i-d:i+d,j-d:j+d);
subValue = pixValue-newI(i,j);
S = exp(-subValue.^2/(2*sigma(2)^2));
H = S.*D;
resultI(i-d,j-d) = sum(pixValue(:).*H(:))/sum(H(:));
end
waitbar(i/m);
end
close(h);
end
function resultI = BilateralFiltColor(I,d,sigma)
I = applycform(I,makecform('srgb2lab'));
[m n ~] = size(I);
newI = ReflectEdge(I,d);
resultI = zeros(m,n,3);
width = 2*d+1;
%Distance
D = fspecial('gaussian',[width,width],sigma(1));
% [X,Y] = meshgrid(-d:d,-d:d);
% D = exp(-(X.^2+Y.^2)/(2*sigma(1)^2));
S = zeros(width,width);%pix Similarity
h = waitbar(0,'Applying bilateral filter...');
set(h,'Name','Bilateral Filter Progress');
sigma_r = 100*sigma(2);
for i=1+d:m+d
for j=1+d:n+d
pixValue = newI(i-d:i+d,j-d:j+d,1:3);
%subValue = pixValue-repmat(newI(i,j,1:3),width,width);
dL = pixValue(:,:,1)-newI(i,j,1);
da = pixValue(:,:,2)-newI(i,j,2);
db = pixValue(:,:,3)-newI(i,j,3);
S = exp(-(dL.^2+da.^2+db.^2)/(2*sigma_r^2));
H = S.*D;
H = H./sum(H(:));
resultI(i-d,j-d,1) = sum(sum(pixValue(:,:,1).*H));
resultI(i-d,j-d,2) = sum(sum(pixValue(:,:,2).*H));
resultI(i-d,j-d,3) = sum(sum(pixValue(:,:,3).*H));
end
waitbar(i/m);
end
close(h);
resultI = applycform(resultI,makecform('lab2srgb'));
end