Describe what the following MATLAB code does. The original function name has bee
ID: 3673803 • Letter: D
Question
Describe what the following MATLAB code does. The original function name has been replaced by fname. Insert the right line of code where it says "%comment taken out,"
function [gx,gy]=fname(IM,sigma)
%(comment taken out)
% [gx,gy]=fname(IM,sigma) (comment taken out)
%
epsilon=1e-2;
halfsize=ceil(sigma*sqrt(-2*log(sqrt(2*pi)*sigma*epsilon)));
size=2*halfsize+1;
%(comment taken out)
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))));
%(comment taken out)
hy=hx';
%(comment taken out)
gx=imfilter(IM,hx,'replicate','conv');
gy=imfilter(IM,hy,'replicate','conv');
function y = gauss(x,sigma)
%(comment taken out)
y = exp(-x^2/(2*sigma^2)) / (sigma*sqrt(2*pi));
function y = dgauss(x,sigma)
%(comment taken out)
y = -x * gauss(x,sigma) / sigma^2;
Explanation / Answer
function [gx,gy]=fname(IM,sigma)
%fname Gradient using first order derivative of Gaussian.
% [gx,gy]=fname(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;