Hi Georg
What I was considering was this: First, calculate the median of each raw or column, and make a vector of these values. Then, take the fourier transform of that vector, and supress high frequencies (I may use the code of the optimal notch filter I'm thinking of). After the inverse FFT, calculate the differences to the old vector, and use that as an additive value for the complete image.
This sounds fast to implement, but I doubt that a RTP would be accurate...
I hope that this procedure would be more robust to artifacts than a 2D FFT filtering process.
BTW, I may also try to use a "training" image, to calculate the correction, and then apply the difference vector to the target image, so it may yield better results in Bob's problem.