Posted by
Kyle Michael Douglass on
URL: http://confocal-microscopy-list.275.s1.nabble.com/Measuring-noise-characteristics-of-sCMOS-cameras-tp7585913.html
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Hi everyone,
This is a rather long and technical post which comes down to a few
questions, so I am providing a "too long; didn't read" first to
summarize. I'm hoping that some of you will find this topic interesting
and be able to reply.
tl;dr: How flat should the illumination be when measuring the photon
response curve of an sCMOS camera? Why should the illumination pattern
be so uniform when each sCMOS pixel can be thought of as an independent
sensor?
I am returning to work on a minor problem that has interested me for
some time. I work in localization microscopy (STORM/PALM/PAINT) and have
been using sCMOS cameras for the past two years with good results. To
precisely localize the single molecule emissions, we take into account
the pixel-dependent noise characteristics of our sensors, incorporating
the measured characteristics of the sensor into the maximum likelihood
estimation of a fluorescent molecule's position. This estimation
procedure was--as far as I know--first described in Huang et al., Nature
Methods 10, 653 (2013), doi:10.1038/nmeth.2488.
To do the characterization requires measuring three quantities for each
pixel of our cameras:
1. the offset (average ADU count under zero illumination)
2. the read noise (variance of the ADU counts under zero illumination)
3. the gain (the number of photoelectrons per ADU when the camera is in
the linear response regime)
The offset and read noise are trivial to measure. To measure the gain,
however, we capture a few tens of thousands of camera frames with the
camera chip under uniform illumination at different light intensities
and follow the mathematical operations described in the supplement to
the paper cited above.
My questions are:
1. Why does the illumination need to be flat when we are measuring the
gain by observing fluctuations in the pixels' ADU counts in time, not in
space? I can understand why illumination non-uniformities would lead to
errors when measuring the noise of a CCD chip. For CCD's, I believe that
one typically treats each pixel as an independent sample of the noise
from the entire chip, so one inherently assumes that the photon shot
noise is uniform across the sensor. However, each pixel is only compared
to itself when measuring the gain of an sCMOS sensor in the manner
described above, so why does it matter that each pixel receives the same
light intensity?
2. How flat is "flat enough" for this calibration procedure? With a
smart phone screen set an optimum distance from the bare camera port and
carefully rotated into position, I can get about 97% uniformity across
the whole chip by simply by displaying gray scale images. Most of the
non-uniformity appears at the corners of the chip where I think
shadowing from the opening in the camera's housing is decreasing the
light intensity slightly. The calibrations I get from this method allow
me to obtain a localization precision that I independently measured from
sparsely distributed dye molecules to be between 8 and 12 nm, which is
in line with published STORM results. When measuring tiny clusters of
proteins, the scatter plots of the localizations match the overall
shapes of their widefield images quite well.
However, a recent paper by Li et al., J. Innov. Opt. Health Sci. 09,
1630008 (2016), doi:10.1142/S1793545816300081, states that one needs
better than 99% uniformity to avoid introducing significant bias into
the noise measurements. Furthermore, the engineers at one of the big
camera manufacturers once told me I shouldn't even bother trying to do
the noise characterization myself since I wouldn't be able to get the
required level of uniformity for an accurate characterization. (In
fairness, they sell the characterization process as a service.)
Unfortunately, I have been unable to find satisfactory answers to these
questions. So far, my results seem to suggest that my calibration is
good enough, but I wonder if someone else can offer their input.
Thanks!
Kyle
--
Kyle M. Douglass, PhD
Post-doctoral researcher
The Laboratory of Experimental Biophysics
EPFL, Lausanne, Switzerland
http://kmdouglass.github.iohttp://leb.epfl.ch