On Mon, 12 Sep 2011, Roman Haefeli wrote:
Am I right in thinking, that the Mode would detect the minor part (with all the exact same color values) as the most prevalent color,
[...]
How would an algorithm work, that would take into account that all the pixels from the major part are very similar and thus would detect a mix of those as the most prevalent color?
It depends...
a strict Mode with smallest histogram bins (one per value) will find the minor part.
a strict Mode with big histogram bins (one for 16*16*16 values, for example) will find the major part only if their values don't overlap several bins, which is some kind of vote-splitting.
but if you do a Mode-like thing with smallest histogram bins AND a convolution by a window, you will get the major part in all circumstances, without «posterisation» artifacts.
however, if you don't want to make a 3-D histogram data structure taking 64 megs and a lot of CPU for applying a 3-D blur on that, you have to get trickier than that... does anyone have any ideas how to find a «blurry Mode» without using much RAM & CPU ?
| Mathieu Bouchard ---- tél: +1.514.383.3801 ---- Villeray, Montréal, QC