matlab-基于matlab实现图像的双边滤波去噪和三边滤波去噪仿真-源码

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 %更多关于matlab和fpga的搜索“fpga和matlab”的CSDN博客: %matlab/FPGA项目开发合作 %https://blog.csdn.net/ccsss22?type=blog %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % 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); 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. 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 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);