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PO
 

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    <p>How about calculating a "density" value for each pixel to start with, based on its proximity to all the other pixels. Then, repeatedly remove the most "dense" pixel until you're below p% remaining in the list. </p> <p>You'd need to do the distance calculation to determine density between any given two points at most twice. First time would be when you build the original list - each pixel would need to be compared with each other pixel. Second would be when you remove a pixel from the list - you'd have to calculate the removed one against each one remaining in the list. This is to account for density values changing as each pixel is removed - for example, 2 pixels directly next to each other would have a very very high value, but once one is removed, the remaining one might have a very low value.</p> <p>Some quick pseudocode (note that in this example, higher density areas have a low number)</p> <pre><code>For I = 0 to MaxPixel For J = I to MaxPixel PixelDensity[I], PixelDensity[J] += DistanceBetween(Pixels[I], Pixels[J]) While PixelDensity.Count &gt; TargetCount RemovePixel = IndexOfSmallest(PixelDensity) ForEach I in PixelDensity PixelDensity[I] -= DistanceBetween(Pixels[I], Pixels[RemovePixel]) PixelDensity.Remove(RemovePixel) </code></pre> <p>If memory is less of a concern than calculation time, you can also store the distance between any two points in a simple 2d array. Also, instead of simple distance, it might be helpful to make the distance calculation exponential - that would avoid something like having two points almost on top of each other, but far away from everything else, and having both make it through.</p>
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    1. POAlgorithm for spread-out 2D point distribution
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    1. COIt sounds like it might work, but the iterations and floating-point calculations might make it slow.
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    2. COYeah, I'm not really sure what size data set you're dealing with. Is there possibly a fixed precision 'filter' type operation you can run when deciding what points to compare? For example, you can say "If these points are over Z distance apart on either the X or Y axis, they're far enough apart to ignore and not do the floating point calculations". Could save you some computation time with next to no effect on accuracy.
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