Author Topic: Non-linear Dark current  (Read 984 times)

Offline Stonius

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Re: Non-linear Dark current (Solved)
« Reply #15 on: 2018 December 09 23:54:45 »
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.

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 32?S to make the bias field. It should be better.

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."