Hey Michael On Tue, Feb 7, 2012 at 4:47 AM, Michael Aye <kmichael.aye@gmail.com> wrote:

I am searching for the best way of doing blob detection in my noisy planetary image data but I just can't find the egg-laying woolen milk-giving pig (german proverb) that would solve all my problems, but then again it wouldn't be called research, if there's nothing to research, right? ;)

I played around with your images in http://dip.sun.ac.za/~stefan/dpt/ just to get a feel for what we're dealing with here. A first result: http://mentat.za.net/refer/aye_planet0.png http://mentat.za.net/refer/aye_planet1.png This technique, specifically, is a non-linear filter, but I think you should be able to achieve the same with a simpler pipeline: 1) Filter out the image noise 2) Find structures of the appropriate range of sizes in the image (maybe using difference of Gaussians or other blob detection) 3) Threshold If you have enough examples of the kind of blobs you're trying to find, you can train a classifier to set thresholds. Otherwise, try to incorporate any knowledge you have from beforehand (i.e., the blobs are roughly X in size, roughly Y in colour, roughly Z in shape). Keep us up to date with your progress, and thanks for the interesting discussion. Cheers Stéfan