雙邊濾波與一般的高斯濾波的不同就是：雙邊濾波既利用了位置信息<or 幾何信息——高斯濾波只用了位置信息>又利用了像素信息來定義濾波窗口的權重。
像素值越接近，權重越大。雙邊濾波會去除圖像的細節信息，又能保持邊界。
對於彩色圖像，像素值的接近與否不能使用RGB空間值，雙邊濾波的原始文獻建議使用CIE顏色空間。
代碼如下：
function resultI = BilateralFilt2(I,d,sigma)
%%%
%Author：LiFeiteng
%Version：1.0——灰色圖像 Time：2013/05/01
%Version：1.1——灰色/彩色圖像 Time：2013/05/02 2013/05/05
%d 半窗口寬度
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
