Gaussian.rar_gaussian_matlab gaussian_matlab image_transform_tra

function [gx,gy]=gaussgradient(IM,sigma) %GAUSSGRADIENT Gradient using first order derivative of Gaussian. % [gx,gy]=gaussgradient(IM,sigma) outputs the gradient image gx and gy of % image IM using a 2-D Gaussian kernel. Sigma is the standard deviation of % this kernel along both directions. % % Contributed by Guanglei Xiong (xgl99@mails.tsinghua.edu.cn) % at Tsinghua University, Beijing, China. %determine the appropriate size of kernel. The smaller epsilon, the larger %size. epsilon=1e-2; halfsize=ceil(sigma*sqrt(-2*log(sqrt(2*pi)*sigma*epsilon))); size=2*halfsize+1; %generate a 2-D Gaussian kernel along x direction for i=1:size for j=1:size u=[i-halfsize-1 j-halfsize-1]; hx(i,j)=gauss(u(1),sigma)*dgauss(u(2),sigma); end end hx=hx/sqrt(sum(sum(abs(hx).*abs(hx)))); %generate a 2-D Gaussian kernel along y direction hy=hx'; %2-D filtering gx=imfilter(IM,hx,'replicate','conv'); gy=imfilter(IM,hy,'replicate','conv'); function y = gauss(x,sigma) %Gaussian y = exp(-x^2/(2*sigma^2)) / (sigma*sqrt(2*pi)); function y = dgauss(x,sigma) %first order derivative of Gaussian y = -x * gauss(x,sigma) / sigma^2;