Slithe

For a school project, I need to think up some (hopefully easy) ways to compress (and decompress) images. I have looked at JPEG's algorithm, but it seems like much too much work to implement. This is just an assignment, so I was trying to think of algorithms that would be easier to implement in Matlab.

Lately, I have been trying to compress a grayscale image by transforming it into frequency space with a Fourier Transform. Then I would examine each value of the transformed matrix and, if the value was small enough, I would just set it zero. I would then use run-length-encoding to pack all the zeroes. However, when I decoded (i.e. unpacked and transformed back to pixel space) the image, pretty much all the values were zero (i.e. the image was all black); however, most values in frequency space were not zero. What am I doing wrong?

Here is my Matlab code. It takes as input a 3-d matrix that stores red green and blue values.

function out = FFTCOMPRESS( in )
x = length(in(1,)/3
y = length(in(:,1))
fr = fft2(in(:,:,1));
fg = fft2(in(:,:,2));
fb = fft2(in(:,:,3));
myout = zeros(1, 5+4*y*x*3);
myout(1) = x;
myout(2) = y;
myout(3) = 6;
for ii=1:y,
   for jj=1:x,
       if fr(ii,jj)<10
           fr(ii,jj)=0;
       end
       if fg(ii,jj)<10
           fg(ii,jj)=0;
       end
       if fb(ii,jj)<10
           fb(ii,jj)=0;
       end
   end
end
n = 6
nz = 0
for jj=1:x,
   for ii=1:y,
       if nz ~= 0,
           if fr(ii,jj)==0
               nz=nz+1;
           else
               myout(n)=0;
               myout(n+1)=nz;
               myout(n+2)=fr(ii,jj);
               nz=0;
               n=n+3;
           end
       else
           if fr(ii,jj)==0
               nz=nz+1;
           else
               myout(n)=fr(ii,jj);
               n=n+1;
           end
       end
   end
end
nz=0;
myout(4)=n;
%Do the same think for fg & fb - I ommited this part.
out=myout(1:(n-1));

Also, does anyone have any other good ideas about how I could easily compress images? Furthermore, does anyone know of a good way to compare the quality of a compressed image with its original?