How did you correct for it? Did you just nonlinearly scale the final picture or did you scale the axis on the spiral itself and then sampled the result?
I was producing grey scale images where each pixel represented a block of numbers. The count in each block was divided by the density of primes (1/log(n)) at the center of the block.
However, this actually made the middle turn grey, because even though the mean value of each pixel was the same, the variance wasn't. So then I corrected for this by calculating a "z-score" instead.
But like I mentioned before, it didn't turn up any interesting patterns.
I guess it specifically didn't turn up interesting patterns because
a) you correct for density
b) the distribution of primes is "noisy" (which is why they're so puzzling) and by averaging out the noise you get a fairly flat distribution
