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Dear all

Thank you for your replies.
I had also thought of using deconvolved images as noise free images 
(estimation of original), but decided not to since the deconvolution 
'erodes' objects by the PSF, hence causing objects to be smaller and have 
different intensities. It might be possible to normalize the latter, but I 
fear the shape adjustment will cause a bias in noise calculation.
It seems the best way must be to use the relation of the detector gain (CCD 
or PMT) with the photon flux.
But as I want to compare with the synthetic images which are independent of 
detector characteristics, I would prefer a way to directly compare the 
images purely from image variables.
A variance estimation over small neighbourhoods throughout the image might 
roughly give an idea of noise, but then again might be skewed by border 
regions?

Winnok


______
ir. Winnok De Vos
Research Assistant

dep. Molecular Biotechnology
Faculty of Bioscience Engineering
Ghent University
Coupure links 653
9000 Ghent
Belgium

tel 0032.(0)9.264.59.71
fax 0032.(0)9.264.62.19
www.molecularbiotechnology.ugent.be
----- Original Message ----- 
From: "Alessandro Esposito" <[log in to unmask]>
To: <[log in to unmask]>
Sent: Friday, July 13, 2007 11:05 AM
Subject: Re: SNR estimation of a single image


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It could be useful the following:

"The Role of Photon Statistics in Fluorescence Anisotropy Imaging" by Lidke
et al.

They use multiple images of the same object to compute a variance from which
you may infer the number of collected photons in the assumption that only
poissonian noise is present.

Cheers,

Alessandro
-- 
Dr. Alessandro Esposito
Laser Analytics Group - Department of Chemical Engineering
University Cambridge
CV: home.quantitative-microscopy.org
Web: wikiscope.org