Why delete high frequence in fft return the area of the most changes?
This line of yours


  delete the component with magnatude compare to DC component(=2.5e5),
  i.e. if Af(i,j)>1e3 , then Af(i,j)=0


indicates an effective highpass filter on the typical smooth image data. 

Indeed for typical smooth images high, frequency coefficients are generally (but not always) smaller in magnitude compared to the low frequeny coefficients. So deleting large magnitude coefficients will effectively delete low frequency coefficients. But this is not exactly same thing with deleting low frequency coefficients directly. neverthless, such an operation would return mostly a darkened image with certain edges and contours outlined, essentially a very a primitive edge detection exemplified with the following code:

I = im2double(imread('Lena.bmp'));
figure,imshow(I);

Ik = fft2(I);
th = 100;
Ik( abs(Ik) &gt; th) = 0;
figure,imshow( 3*real(ifft2(Ik)));


with the result: