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  #21  
Old 03-12-2018, 09:32 AM
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RickS (Rick)
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Hi Markus,

I started doing the new analysis I was planning for my ASI1600mm Pro. As a first step I captured multiple bias and dark frames at different durations and plotted the average ADU for each duration. Dark current is quite linear and behaves as expected, but only for durations of a few seconds or more. For short durations weird stuff happens. Note that short duration frames are handled completely by the camera but the capture software does timing for longer frames...

Cheers,
Rick.
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  #22  
Old 03-12-2018, 10:09 AM
glend (Glen)
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Quote:
Originally Posted by RickS View Post
......
The chap that did the ASI294 analysis found that adding dummy 1 second frames between each calibration frame removed some unexpected variation so I'm doing that this time around to see if it also helps with the ASI1600.

Cheers,
Rick.
Rick, it's not a good idea to apply ASI294 (IMX294) calibration tricks towards the ASI1600, they are totally different in relation to calibration practice. It is worth reading through Jon Rista's CN Beta Test threads on both the ASI294 and 1600.
The IMX back lit architecture is an impediment to even substrate cooling, giving rise to colour gradient abnormalities, it is also subject to significant unmanaged AMP glow problems. ZWO has gone so far as to changing their marketing strategy for the 294, pitching it as an EAA camera (where it's sensitivity, with high frame video) negates the issues that haunt it's long sub AP performance.
So in terms of the original topic, there are big differences in CMOS camera capabilities and operational practices depending on which chip is used.
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  #23  
Old 03-12-2018, 10:42 AM
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Hi Glen,

I have read a lot of threads including the ones you mention and I'm not blindly applying ASI294 tricks to the ASI1600 and assuming they will work.
I'm testing to see what effect they have, if any...

These cameras exhibit some similarities in behaviour but I'm not expecting them to be the same in all aspects.

Cheers,
Rick.
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  #24  
Old 04-12-2018, 09:37 AM
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Added gain 72 to the graphs (72 is max dynamic range for my camera.) As well as plotting mean ADU I have also plotted the mean dark current in electrons.

The "bump" at gain 72 where a 2 second dark has higher ADU than a 3 second dark is odd but the ASI294 does something similar (and even more dramatically.) I might run some numbers at lower gain to see if it becomes more pronounced.

Apart from odd behaviour with short frames everything else looks as you'd expect.

Cheers,
Rick.
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  #25  
Old 10-12-2018, 06:34 PM
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Help measuring CMOS performance (Solved)

For the sake of others following this thread, I got some answers from Chad at ZWO which echoed some of the findings in John Upton's Cloudy Nights thread quoted above.

Apologies if everyone else knew this already. Everywhere I had read seemes to say bias frames should be as short as possible, and that they should then be used as a basis for assessing dark current in longer exposures. As you'll see below, neither is true (at least of this camera - maybe other CMOS cameras behave the same way?)

The trick was not to compare the darks to a bias frame, but to a set of 2 second frames. Attached is the result of that simple change. You can see the graph looks much more like you'd expect.

The thread from ZWO can be found here.

The long and the short of it - When trying to measure dark current per second, the shortest exposure you should use is no less than 2 seconds. A bias frame is no good and will give you the same results I did. In addition, bias frames should be shot at 0.1ms, not 0.000032s as I did (I mistakenly shot at 0.000032 because it's the shortest possible exposure on the 1600. Don't do what I did, it was wrong!).

And if you really want to get technical, you can follow John Upton's advice in post #3 on the above thread and calibrate your Bias frames using a Y intercept of a plot of multiple Dark Frame exposure times.

Relevant bits from Chad and John quoted below.

HI Markus,
We tested the 1600 MM Pro with your method. It has the similar result with yours.
So thanks for your support first.
For the result, we think it may be the following reasons.
When we have an operation, for the circuit, it's like dropping a pebble on a calm water. There will be some disturbance in the circuit. When the gain is large, the disturbance is greatly amplified. For long exposure, there are some different operations with short exposure.
Beside, consider that the short exposure is different with long exposure in the camera, so I think it is better to measure at long exposure. It means you should use 2 seconds exposure time to replace the image of 32uS exposure.
Thanks
Chad

Hi Markus,
For this test, because it is a test about the dark current. If the exposure time is short, we usually think the dark current is not the main noise. the main noise should be read noise and other noise. That is why I suggest that use the 2 second to make the test.
But for bias field, usually, we want to use it to calibrate the read noise. So it should not a long exposured image. Also consider the fluctuations of the circuit, I suggest that you can use 0.1ms instead of 32μS to make the bias field. It should be better.
Thanks
Chad

And from John Upton;

"The convoluted process for scaling Dark Frames begins with having a Bias and Dark Frame library taken at the same Temperature, Gain, and Offset. The first step is to determine the Dark Current slope and Y intercept of a plot of multiple Dark Frame exposure times. My Dark Library uses 50 each 0, 60, 120, and 240 second exposures. The data for Mean ADU values of each average integrated frame exposure is plotted against Exposure time in a spreadsheet. The slope and Y intercept of such a graph is easily obtained using the LINEST() function. The results will give us the parameters we are looking for. The Slope gives us the Dark Current rate for the sensor while the Y intercept gives us the equivalent Mean ADU value for a CCD-like Bias Frame taken at 0 seconds exposure.

This Dark Frame-derived Bias Mean just tells us what the mean of our camera Bias should have been. It is just a number and contains no information whatsoever about the pattern noise from our camera. Our actual Bias Frame from the camera will have the pattern noise we need but the Mean value is off what it should have been. The second step is to subtract the difference between the Mean of the Bias image and the Y intercept on a pixel by pixel basis. This can be done using PI PixelMath with an equation of $T (mean($T) Y_Intercept_Of_Dark_Plot). After this adjustment, we now have an Adjusted Bias that can be used to calibrate a Dark Frame so that it can be scaled.

Scaling the Dark Frame for use in calibrating our lights can best be done using PixelMath again. Here, we simply scale the Dark by the ratio of exposure times between what we have and what we need. For example if we have Dark Frames in our library for 60 and 120 seconds but took our target lights at 90 second exposures, we would use PixelMath on our 120 second Library Dark Frame and write ($T - Adjusted_Bias) * (90 / 120). This gives us the scaled Dark Frame for use in the ImageCalibration for our lights. We would also plug in the Adjusted Bias as the Bias file in ImageCalibration. A similar pre-calibration process should be used on the Flat Frame we will use for ImageCalibration."
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  #26  
Old 11-12-2018, 06:31 PM
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I wanted to post one final graph which in completely unsurprising news looks very much like RickS's graph.

This has helped me determine the most accurate bias frame possible.

The time on the X axis is not to scale, but it allows you to see the way the camera operates at different exposure lengths.

You can see that the shortest possible exposure does not yield an exposure that is indicative of the kind of read noise you will get in longer exposures.

I verified this by doing integrations of 100 frames for each time, constructing a superbias of each and comparing them. And they were very different. The STF brings them all up to the same level, of course, but you can see that the noise patterns are quite different.

0.0001s has a glow on the left of frame.

0.001s develops a dark gutter on the right, but corresponds to the lowest actual noise levels on the graph. (but for the STF, this image would look darker).

At 1.5s there is a glow to the right that corresponds to amp glow, which continues along the top and bottom edges of frame.

Only once exposures exceed 2 seconds do the bias frame stabilise, as seen in the graph, where all values over 2s are in a straight line.

So in essence, bias frames less than 2 seconds long are unlikely to be representative of the actual bias pattern noise found in longer exposures.

If, for example, you shoot flats for NB that are a few seconds long, and you rely on scaling of a bias to subtract read noise from the flats (rather than actually shooting flat darks that are the same length as the flats themselves), you could be doing yourself a disservice.

Cheers

Markus
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