The basic idea is that just as an audio signal can be decomposed into frequency components, an image can be decomposed into frequency components, but in two dim

The basic idea is that just as an audio signal can be decomposed into frequency components, an image can be decomposed into frequency components, but in two dimensions. (Imagine stripes of varying frequency and direction instead of sine waves of various frequencies.) Sharp edges in an image have high frequency components, just like a sharp transition in an audio signal. Filtering the high frequencies will blur the image, while filtering low frequencies will enhance edges. This is very oversimplified, but will hopefully give you a bit of an idea. I encourage people to learn more about Fourier theory, because it explains a lot. One introductory page that you may find useful is: http://cns-alumni.bu.edu/~slehar/fourier/fourier.html http://cns-alumni.bu.edu/~slehar/fourier/fourier.html