- #1

Artlav

- 162

- 1

I'm trying to implement it, and got lost in the mathematics.

http://graphics.cs.kuleuven.be/publications/LVLD10PISTE/

The outline of the algorithm is thus:

We start with a noise-like photo.

Do a 2D DFT of it:

Compute the power band coefficients and reconstruct the image with wavelet noise:

Wavelet noise is band limited, which makes it a good base block for such synthesis:

That's the theory.

In practice, i can't figure out the formula for the coefficients.

Formula (E is the input image):

Definition of the power band:

What does it mean?

Should i sum all the magnitudes of the elements in each band?

This gives me nonsense if i divide it by the amount of elements, and randomly unscaled value if i don't (that's the above picture, guesstimately scaled).

If i sum the real parts of the elements, then i get wildly wrong and out of scale figures. Normalising them also gives me something plausible.

And so on, for any way i can think of.

I guess i misunderstand something in the notation.

Does the integral sign means summing here?

Or how should i read it?

That's basically the question - what does it mean?

Bonus question - anyone heard of this method being used somewhere? A working implementation to peek at would be nice.