%
% ASSIGNMENT 3 - SIMPLE CFAR detector
%
% INPUTS:
%
% image_data - array of doubles
% k_std - number of standard devaiations for threshold (eg. 2.5).
% smin - is minimum allowable estimate for the standard deviation
% wsize - a 1x2 array of row and column size of neighbourhood (eg. [7 9])

function cfar_result = simple_cfar(image_data,k_std,smin,wsize)

% force 2d array of doubles
if (isa(image_data,'uint8'))
image_data=double(image_data(:,:,1))/255;
end
% handle single size term
if (length(wsize)==1)
wsize(2)=wsize(1);
end
% force odd sized window sizes 3,5,7,9 etc
wsize=max(3,2*floor(wsize/2)+1);

% initialise output
cfar_result = zeros(size(image_data));

r = wsize(1);
c = wsize(2);
n = size(image_data);
for i = 1:n(1)-r
for j = 1:n(2)-c
   I1 = image_data(i,j:j+c);
   I2 = image_data(i+r,j:j+c);
   I3 = image_data(i:i+r,j);
   I4 = image_data(i:i+r,j+c);
   I = [I1 I2 I3' I4'];
   m = mean(I);
   sd = max(smin,std(I));
   P = image_data(i+(r-1)/2,j+(c-1)/2);
   if abs(P-m)/sd > k_std
         cfar_result(i,j) = 1;
   end
end
end

return

The DFT of a 2D image can be written in terms of magnitudes and pha...