Hmm. I was dealing with a problem like this the other week: I had a set of images where the useful data I needed to extract was lines, and the stuff I most needed to get rid of was lines too, but stronger. The solution I hit on in the end was to sobel filter the images, take the histogram of the image which had lots of discrete chunks in, the first of which has all the lines in, the others have just the bad lines in, find the first zero in it, and replace the pixels whose local average of the sobel filtered version was bigger than where the first zero came, with the image mean. This did bugger all good, because I just got reconstructions that were a blank space of image mean, because all my images contained a lot of pixels at that value so my strongest convergence point was there and not at the actual answer. Bollocks.

Anyway yes. Let me think...I would get it to plot an initial histogram, take some statistics out of it like how much area it's got under it by a certain amount of time, calculate an optimum spacing and set that to be the histogram binsize for the proper graph. This depends on me being able to set the histogram binsixe, however.