http://confocal-microscopy-list.275.s1.nabble.com/Readout-noise-in-sCMOS-cameras-tp7588012p7588021.html
I just have read the all the contributions, because I returned to my office today and no access to my mailbox the last two days.
I was referring to the fact, that the dark noise distribution in sCMOS can be approximated by a Gaussian, but by the shape it is visible, that it is not, because of that "tail" with the high noise pixels. Reasons for that are manifold, some related to the semiconductor manufacturing process, to the chosen technology (surface channels vs. buried channels), and some of them simply to the high number of parallel readouts, because it doesn't matter how precise you handle the process, the gains of the all the transistors, the resistor an capacitor values, the A/D converters all of them might have some slight even small differences, which might contribute to the noise distribution.
This in fact was a big advantage of CCDs, because they had a serial readout, all charge packages generated by each individual pixel, had to pass the same readout circuit, therefore they all received more or less the same noise contribution by the readout circuit, and this resulted in a noise distribution which could be approximated by a Gaussian distribution.
Concerning the different types of noise, I could nothing add to what James B Pawley and Kyle Douglass have said, and supporting that everybody who is interested in these topics should have a look to the EMVA1288 standard. If you are more interested in the general noise sources you might want to have alook at the webinars and publications by Prof. Albert Theuwissen or the papers of Jim Janesick.
Dr. Gerhard Holst
USt. ID-Nr. / VAT: DE128590843, Registergericht / Register court: Regensburg HRB 9157
Sitz der Gesellschaft / Registered office: Kelheim, Vorstand / Chairman: Dr. Emil Ott
Gesendet: Dienstag, 6. März 2018 19:52
Thanks everyone for the insightful remarks, and Kyle for the comment about temporal versus spatial non-uniformity.
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> Dear Jeremy,
>
> Of course you correct.
>
> I stated it as I did because I find that people who correctly
> understand that the signal-to-Poisson Noise ratio increases with the
> sqrt of the signal level forget that the absolute value of the
> uncertainty in the signal level increases with the sqrt of the signal
> level, i.e., they are surprised to see that the “grass” on the signal
> of apparently uniform bright areas is much greater than that on dark areas.
>
> While it may be convenient to estimate that the noise in low contrast
> widefield image from a CCD can be approximated as being Gaussian, this
> really is not true when applied to images from, for instance, an
> slow-scan CCD image from a confocal. In the latter, many pixels will
> be essentially black and in these pixels, the noise will be Gaussian
> and represent the read noise of the charge-to-voltage converter (much
> of which is Johnson noise related to the electron statistics of small,
> fairly constant currents). However, it would be a mistake to think
> that this same Gaussian accurately defines the uncertainty of signals
> from the brighter parts of the image (>100 photoelectrons?).
>
> sCMOS has a whole raft of other noise terms and as noted the noise in
> their output is poorly estimated by a Gaussian, particularly on images
> having high-contrast.
>
> Great sensors though!
>
> JP
>
> James and Christine Pawley, 5446 Burley Place, Box 2348, Sechelt BC,
> Canada, V0N3A0
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>
>
> On Mar 6, 2018, at 2:47 AM, Jeremy Adler
> <
[hidden email] <mailto:
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>
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>
>
> Dear James,
> a minor point from your interesting post.
>
> "Poisson Noise get bigger as the signal increases!"
>
> This is true as an absolute measure of the size of the variation
> around the mean but your statement could be misinterpreted as a
> preference for detecting fewer PEs.
> Perhaps adding - but is smaller as a fraction of the signal
> An average of 16 PEs has a standard deviation of 25% while for 256
> PEs the SD drops to around 6% and to 3% for 1024.
>
>
> Jeremy Adler
> IGP, Uppsala U, Sweden
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> -----Original Message-----
> From: Confocal Microscopy List
> [mailto:
[hidden email]]
> On Behalf Of JAMES B PAWLEY
> Sent: den 6 mars 2018 07:22
> To:
[hidden email]
> Subject: Re: Readout noise in sCMOS cameras
>
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> Dear Sripad,
>
> In a CMOS chip, every pixel has its own read amp. All of these vary
> slightly in gain and DC-offset. So the raw output from a a black (no
> light) image would have a noise term related to how much the offsets
> of the pixel amps varied and a uniform white image would have Poisson
> noise on the photo charge plus a noise term mostly related to the
> variation in the gains of the pixel amplifiers.
> In an sCMOS chip to these uncertainties must be added variations in
> the gain and offer of the 4,000-plus separate ADCs mounted at the
> edges of the chip. An effort is made to correct for the
> multi-amplifier and multi-digitizer noise by “flat fielding” the raw
> data from the chip using data from previous “black” and “white”
> images, The system works quite well but as the white image always
> involves a lot of charge, its Poisson noise (sqrt of n) is large and
> this can skew the results. So can using the chip at a different
> temperature, dwell time or pixel clock than was used for the “black”
> and “white” images. Other sources on non-“Gaussian” noise include
> “hot pixels” (perhaps leaky photodiodes that are sometimes flagged and removed by the camera system software).
>
> Indeed, the noise spectrum in these low-light systems is almost never
> “Gaussian”. Even if the electronic noise (that signal variation which
> becomes evident when reading the same pixel with no light signal)
> seems Gaussian, it is usually caused by Poisson Noise (Or Johnson
> noise) affecting the small number of electrons that constitute the
> (fairly table currents passing through the elements of the charge
> amplifier. And of course, at signal levels of more than a few dozen
> photoelectrons, Poisson Noise on the PE number soon dominates most
> other noise sources (not hot pixels).
>
> Gaussian noise is just easier to think about, and easier to model. We
> should remember that in low-light photodetectors, it is almost never
> appropriate. (Poisson Noise get bigger as the signal increases!).
>
> Best,,
>
> JP
> James and Christine Pawley, 5446 Burley Place, Box 2348, Sechelt BC,
> Canada, V0N3A0
[hidden email]<mailto:
[hidden email]>, Phone
> 1-604-885-0840, cell 1-604-989-6146
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>
> On Mar 5, 2018, at 9:54 AM, S Ram <
[hidden email]<mailto:s
>
[hidden email]>> wrote:
>
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> Hello Gerhard,
> This is a slightly off-topic question in connection to your recent
> response to the thread on the choice of sCMOS cameras.
>
> You made a comment that the distribution of noise in sCMOS is not Gaussian.
>
> Can you clarify whether you meant noise during the readout process
> (charge to voltage conversion step)? If it is not Gaussian, what is
> the underlying noise process? Is there any literature that you can point me to?
>
> Thanks.
>
> Sripad
>
>
>