I am having the program for gabor filter with 3 scales and 4 orientation hence there will be 12 gabor filtered images.i have shown the pgm below..can anyone he to take the 12 filtered images as output...

function G=gabor(X1)

M=4; N=3; a=(0.4 / 0.05)^(1/(M-1)); gab=cell(2,2); count=1;

 for m=1:M
     for n=1:N

         W=a^m * 0.05;
         sigmax=((a+1)*sqrt(2 * log(2))) / (2 * pi * a^m * (a-1) * 0.05);
         sigmay1=((0.4 *0.4) / (2*log(2))) - (( 1 / (2 *pi* sigmax))^2); 
         sigmay=1 / ((2* pi * tan(pi/(2*N)) * sqrt ( sigmay1)));
         theta=(n*pi)/N ;

         for ij=1:2
            for i=1:3
              for j=1:3
                    xb=a^(-m) * (i*cos(theta) + j*sin(theta));
                    yb=a^(-m) * ((-i)*sin(theta) + j*cos(theta));
                    phi1=(-1/2) * ((xb*xb)/(sigmax*sigmax) + (yb*yb)/(sigmay*sigmay));
                     if ij==1
                        prob=i;
                    else
                        prob=j;
                    end
                    phi=(1/(2*pi*sigmax*sigmay)) * exp(phi1) *exp(2*pi*W*prob);
                    gab1(i,j)=phi* a^(-m);
              end
          end
         gab{count,ij}=gab1;

        end

          count=count+1;
      end
 end

mskno=1;

for i=1:12 for j=1:2 aa=cell2mat(gab(i,j)); aa=double(aa); mask(:,:,mskno)=aa; mskno = mskno+1; end

    end

for k=1:24

    filterimage(:,:,k)=conv2(X1,mask(k),'same');

end

G=filterimage;

[Thorsten]

I think it does not make much sense to define a Gabor on a 3 x 3 grid because you get a very coarse approximation of a Gabor. If you filter your image with these "Gabors" you may get some unexpected results.