As I test through different method further
- Phair's method (or simple ratio)
- Exponential decay fitting (or exponential ratio, I call)
- Histogram streching,
all these methods are not really satisfactory. so I kept on searching for other methods and I tested something not used often, which is called “Histgram Matching”, and it seems to work better. Bleached images are better be blurred a bit. I might try implementing it as another method for bleaching correction.
Followings are links related to this method, which I referred to.
Histogram equalizaiton theory (by R. Fisher, S. Perkins, A. Walker and E. Wolfart.@ Image Processing Learning Resources).
I also refrred to Digital Image Processing using Matlab“ but it was too simply formulated (and, the matlab function which should be used is indicated but too short).
Paper: “A statistical approach for intensity loss compensation of confocal microscopy images”, Gopinath et al (2007) J. of microscopy ( Link). This paper tries to correct the acquistion bleaching while the image itself is changing a lot (the sample seems to be internalizing cell surface recepter, so from diffuse signal to dotty signals). In case of sequences with less changes in signal shape, the problem is more simple and straightforward, but such dynamic version should be already in our sight. (by the way, I am always amazed by works which Luby-Phelps is involved in. When I found the name on this paper, amazed again…).
CMPUT 206, Instructor: NilanjanRay
(powerpoint slides in PDF)
Java library: source for historam matching is in Burger & Burge website, chapter 5.
"Digital Image Processing: An algorithmic introduction uing Java"