Intensity normalization of image using Python+PIL - Speed issues

Question

I\'m working on a little problem in my sparetime involving analysis of some images obtained through a microscope. It is a wafer with some stuff here and there, and ultimatel

Answer 1

See http://docs.scipy.org/doc/scipy/reference/generated/scipy.misc.fromimage.html#scipy.misc.fromimage

You can say

databack = scipy.misc.fromimage(pixback)
rmax = numpy.max(databack[:,:,0])
gmax = numpy.max(databack[:,:,1])
bmax = numpy.max(databack[:,:,2])

which should be much faster than looping over all (r,g,b) triplets of your image. Then you can do

dataold = scip.misc.fromimage(pixold)
r = dataold[:,:,0] / (pixback[:,:,0] * rmax )
g = dataold[:,:,1] / (pixback[:,:,1] * gmax )
b = dataold[:,:,2] / (pixback[:,:,2] * bmax )

datanew = numpy.array((r,g,b))
imnew = scipy.misc.toimage(datanew)

The code is not tested, but should work somehow with minor modifications.