http://confocal-microscopy-list.275.s1.nabble.com/Measuring-noise-characteristics-of-sCMOS-cameras-tp7585913p7585939.html
for the light source. For photo enlargers, a stabilizing transformer
Marc R. Reinig
W. M. Keck Center for Adaptive Optical Microscopy
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> Good point,
> as a matter of fact, even in standard photon transfer curve measurements,
> the fixed pattern noise becomes apparent at several thousand photons per
> pixel. We're talking about couple hundreds here.
> But it's hard to tell how large frame-to-frame and longer term fluctuations
> are still OK given the large number of frames analyzed (tens of thousands)
> and the non-trivial method of gain determination in the Joerg's paper (least
> square estimation). On the other hand, given the photon noise standard
> deviation is 5% at 400 photons, 1% (max) illumination intensity fluctuation
> does not sound like a gross overkill...
> Best, zdenek
> Btw, while my PC monitor LED backlight shows nice PWM at 1.2 kHz, my
> smartphones produced steady illumination (no fluctuations up to 50 kHz).
>
> ---------- Původní zpráva ----------
> Od: Gerhard Holst <
[hidden email]>
> Komu:
[hidden email]
> Datum: 26. 10. 2016 11:14:42
> Předmět: AW: AW: Measuring noise characteristics of sCMOS cameras
>
>
> Hi Kyle,
>
>
>
> may I ask 1% of what? Further, including poisson noise? I mean the
> fluctuations go with the square root of the number of photons.
>
>
>
> with best regards,
>
>
>
> Gerhard
>
> ___________________________
>
> Dr. Gerhard Holst
>
> Science & Research
>
> PCO AG
>
> Donaupark 11
>
> 93309 Kelheim, Germany
>
> fon +49 9441 2005 36
>
> fax +49 9441 2005 20
>
> mob +49 172 711 6049
>
>
[hidden email]
>
> www.pco.de
>
>
>
> Von: Confocal Microscopy List [mailto:
[hidden email]] Im
> Auftrag von Kyle Douglass
> Gesendet: Mittwoch, 26. Oktober 2016 17:01
> An:
[hidden email]
> Betreff: Re: AW: Measuring noise characteristics of sCMOS cameras
>
>
>
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>
> Thanks to everyone who has thus far replied to my original e-mail. I realize
> after doing some more reading that I was essentially conflating two
> different "noise" sources into one: fixed pattern noise, for which one
> certainly wants a uniform illumination to measure, and the per pixel gain,
> which is what is measured in the Huang/Bewersdorf paper.
>
> My next question is: what kind of light source is going to provide <1%
> temporal intensity fluctuations? A CW LED pumped into an integrating sphere?
>
> Zdenek: Thanks for the heads up about the PWM driver in the smart phone LED
> backlight. I wouldn't be surprised if this were true. Interestingly, I can
> see aliasing in a live stream from the camera when using a computer monitor
> as illumination (60 Hz refresh rate) but I can not see it with the smart
> phone.
>
> Gerhard: The EMVA 1288 document is absolutely wonderful. Thanks for this.
>
> Seamus: I actually have the book next to me on my desk. Thanks for the
> reminder about the chapter :)
>
> Cheers,
> Kyle
>
>
> On 10/26/2016 03:37 PM,
[hidden email] wrote:
>
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http://www.imgur.com and include the link in your posting. ***** Honestly, I
> hope my Orca Flash does not have microlenses!
>
> But back to Kyle's question.
>
> Joerg Bewersdorf's approach is strictly on pixel basis, the spatial
> uniformity is not critical (97% is more than sufficient), but temporal
> uniformity is important and < 1% intensity fluctuations are not trivial to
> achieve (I could not find this figure in my smartphone's specs :-). Slow
> drift can be easily seen in your images (if you average every 1000 images
> and look at the trends), but short-time fluctuations may be harder to detect
> (beware, there is often some sort of PWM driver for the LED backlight)!
>
> As mentioned in the ref 17 (thanks Seamus for the link) there are many
> sources of "fixed pattern noise" (I don't like the term noise, it's just
> non-uniformity), including different light sensitivity of individual pixels
> or dust on the optics. Joerg's approach does not account for these effects,
> he just intended to bring SCMOSes on par with CCDs. There are more critical
> aspects of localization superresolution microscopy (such as illumination
> uniformity) than dust on the camera window... (but another word of caution,
> smudges on the camera won't be visible during the calibration, but may be
> visible when coupled to the microscope, because the light has fairly low
> etendue / cone angle / numerical aperture at the detector).
>
> Btw, has anyone characterized the new back-illuminated SCMOS cameras (like
> Photometrics Prime 95B)? How do they compare with standard SCMOSes (Zyla,
> Orca)?
>
> Best, zdenek
>
>
> --
> Zdenek Svindrych, Ph.D.
> W.M. Keck Center for Cellular Imaging (PLSB 003)
> University of Virginia, Charlottesville, VA
>
http://www.kcci.virginia.edu/> tel: 434-982-4869
> Annual FRET Workshop:
http://kcci.virginia.edu/workshop-2017>
> ---------- Původní zpráva ----------
> Od: Gerhard Holst <
[hidden email]>
> Komu:
[hidden email]
> Datum: 26. 10. 2016 4:49:59
> Předmět: AW: Measuring noise characteristics of sCMOS cameras
>
>
>
> *****
> To join, leave or search the confocal microscopy listserv, go to:
>
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> *****
>
> Hi Kyle,
>
> your question is absolutely reasonable, and in my opinion it doesn't have to
> be. If you google you will find the EMVA1288 standard for measuring and
> representing quality parameters of image sensors and cameras. There is
> described how the gain can be measured. If a linear camera or image sensor
> model can be assumed, and our experience as manufacturer of sCMOS cameras
> proves that, for ease of measurement a relatively homogenous illumination
> should be ok. The standard suggests a diffuse illumination. The homogeneous
> illumination is more important for getting information on the homogeneous
> reaction of the image sensor, means to determine the so called
> photo-response-non-uniformity. To determine the gain the photon transfer
> curve is usually measured, and this is the variance versus mean signal, and
> the variance is usually calculated from the difference of two images,
> therefore if the pixel have more or less the same brightness, that's good
> enough.
> Alternatively you might use the Fe+55 method. Here the knowledge about the
> charge generation if silicon is hit be x-ray quants is used. We have done
> that and in case of the sCMOS image sensors in delivers the same results
> like the PTC curve approach.
>
> If you take an integrating sphere with diffuse reflection and scattering,
> like suggested in the EMVA1288 that would be good enough in my opinion.
> Since the image sensors have micro lenses, directed radiation is not such a
> good idea.
>
> with best regards,
>
> Gerhard
> ___________________________
> Dr. Gerhard Holst
> Science & Research
> PCO AG
> Donaupark 11
> 93309 Kelheim, Germany
> fon +49 9441 2005 36
> fax +49 9441 2005 20
> mob +49 172 711 6049
>
[hidden email]
> www.pco.de
>
> -----Ursprüngliche Nachricht-----
> Von: Confocal Microscopy List [mailto:
[hidden email]] Im
> Auftrag von Kyle Douglass
> Gesendet: Mittwoch, 26. Oktober 2016 09:55
> An:
[hidden email]
> Betreff: Measuring noise characteristics of sCMOS cameras
>
> *****
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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.io http://leb.epfl.ch>
>
>
> --
>
> Kyle M. Douglass, PhD
>
> Post-doctoral researcher
>
> The Laboratory of Experimental Biophysics
>
> EPFL, Lausanne, Switzerland
>
>
http://kmdouglass.github.io>
>
http://leb.epfl.ch