数字图像处理-平滑滤波处理

%简单地说: %A为给定图像，归一化到[0,1]的矩阵 %W为双边滤波器（核）的边长/2 %定义域方差σd记为SIGMA(1),值域方差σr记为SIGMA(2) %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Pre-process input and select appropriate filter. function B = bfilter2(A,w,sigma) % Verify that the input image exists and is valid. if ~exist('A','var') || isempty(A) error('Input image A is undefined or invalid.'); end if ~isfloat(A) || ~sum([1,3] == size(A,3)) || ... min(A(:)) < 0 || max(A(:)) > 1 error(['Input image A must be a double precision ',... 'matrix of size NxMx1 or NxMx3 on the closed ',... 'interval [0,1].']); end % Verify bilateral filter window size. if ~exist('w','var') || isempty(w) || ... numel(w) ~= 1 || w < 1 w = 5; end w = ceil(w); % Verify bilateral filter standard deviations. if ~exist('sigma','var') || isempty(sigma) || ... numel(sigma) ~= 2 || sigma(1) <= 0 || sigma(2) <= 0 sigma = [3 0.1]; end % Apply either grayscale or color bilateral filtering. if size(A,3) == 1 B = bfltGray(A,w,sigma(1),sigma(2)); else B = bfltColor(A,w,sigma(1),sigma(2)); end %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Implements bilateral filtering for grayscale images. function B = bfltGray(A,w,sigma_d,sigma_r) % Pre-compute Gaussian distance weights. [X,Y] = meshgrid(-w:w,-w:w); %创建核距离矩阵，e.g. % [x,y]=meshgrid(-1:1,-1:1) % % x = % % -1 0 1 % -1 0 1 % -1 0 1 % % % y = % % -1 -1 -1 % 0 0 0 % 1 1 1 %计算定义域核 G = exp(-(X.^2+Y.^2)/(2*sigma_d^2)); % Create waitbar. h = waitbar(0,'Applying bilateral filter...'); set(h,'Name','Bilateral Filter Progress'); % Apply bilateral filter. %计算值域核H 并与定义域核G 乘积得到双边权重函数F dim = size(A); B = zeros(dim); for i = 1:dim(1) for j = 1:dim(2) % Extract local region. iMin = max(i-w,1); iMax = min(i+w,dim(1)); jMin = max(j-w,1); jMax = min(j+w,dim(2)); %定义当前核所作用的区域为(iMin:iMax,jMin:jMax) I = A(iMin:iMax,jMin:jMax);%提取该区域的源图像值赋给I % Compute Gaussian intensity weights. H = exp(-(I-A(i,j)).^2/(2*sigma_r^2)); % Calculate bilateral filter response. F = H.*G((iMin:iMax)-i+w+1,(jMin:jMax)-j+w+1); B(i,j) = sum(F(:).*I(:))/sum(F(:)); end waitbar(i/dim(1)); end % Close waitbar. close(h); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Implements bilateral filter for color images. function B = bfltColor(A,w,sigma_d,sigma_r) % Convert input sRGB image to CIELab color space. if exist('applycform','file') A = applycform(A,makecform('srgb2lab')); else A = colorspace('Lab<-RGB',A); end % Pre-compute Gaussian domain weights. [X,Y] = meshgrid(-w:w,-w:w); G = exp(-(X.^2+Y.^2)/(2*sigma_d^2)); % Rescale range variance (using maximum luminance). sigma_r = 100*sigma_r; % Create waitbar. h = waitbar(0,'Applying bilateral filter...'); set(h,'Name','Bilateral Filter Progress'); % Apply bilateral filter. dim = size(A); B = zeros(dim); for i = 1:dim(1) for j = 1:dim(2) % Extract local region. iMin = max(i-w,1); iMax = min(i+w,dim(1)); jMin = max(j-w,1); jMax = min(j+w,dim(2)); I = A(iMin:iMax,jMin:jMax,:); % Compute Gaussian range weights. dL = I(:,:,1)-A(i,j,1); da = I(:,:,2)-A(i,j,2); db = I(:,:,3)-A(i,j,3); H = exp(-(dL.^2+da.^2+db.^2)/(2*sigma_r^2)); % Calculate bilateral filter response. F = H.*G((iMin:iMax)-i+w+1,(jMin:jMax)-j+w+1); norm_F = sum(F(:)); B(i,j,1) = sum(sum(F.*I(:,:,1)))/norm_F; B(i,j,2) = sum(sum(F.*I(:,:,2)))/norm_F; B(i,j,3) = sum(sum(F.*I(:,:,3)))/norm_F; end waitbar(i/dim(1)); end % Convert filtered image back to sRGB color space. if exist('applycform','file') B = applycform(B,makecform('lab2srgb')); else B = colorspace('RGB<-Lab',B); end % Close waitbar. close(h);