> The only benefit this has over its contemporaries is that it is tileable. Although, it does repeat making this benefit useless considering that Perlin and Simplex noise are non-repeating and infinite.
Perlin and Simplex are also easily tileable too. Just make your hash function periodic and the resulting noise while tile at the same period.
This is a neat article and a neat technique, but probably not super practical. If you know how synthesizers (like the musical instruments) work, then you can think of Perlin noise as additive synthesize and the article here as subtractive synthesis.
Taking the FFT, modifying frequency amplitudes, and then taking the IFFT is one way to implement a filter. A more direct way is to filter in the time (well, space here) domain using something like a FIR or IIR. In spatial terms, that means applying a convolution filter, which is exactly how most blurring algorithms in programs like Photoshop work.
So, another way to look at this, is that you can generate pretty terrains by taking white noise and blurring it with the right convolution kernel.
Perlin and Simplex are also easily tileable too. Just make your hash function periodic and the resulting noise while tile at the same period.
This is a neat article and a neat technique, but probably not super practical. If you know how synthesizers (like the musical instruments) work, then you can think of Perlin noise as additive synthesize and the article here as subtractive synthesis.
Taking the FFT, modifying frequency amplitudes, and then taking the IFFT is one way to implement a filter. A more direct way is to filter in the time (well, space here) domain using something like a FIR or IIR. In spatial terms, that means applying a convolution filter, which is exactly how most blurring algorithms in programs like Photoshop work.
So, another way to look at this, is that you can generate pretty terrains by taking white noise and blurring it with the right convolution kernel.