Show Posts

This section allows you to view all posts made by this member. Note that you can only see posts made in areas you currently have access to.


Messages - Stonius

Pages: [1]
1
General / Re: Averaging integration doesn't...uh, average
« on: 2018 December 12 21:18:13 »
Thanks Niel, that makes sense. IOW, my manual process was averaging entire frames first, whereas integration averages each pixel location first, hence the difference.

Cheers Mate

2
General / Re: Non-linear Dark current (Solved)
« 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.
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 32?S 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."

3
General / Re: Non-linear Dark current
« on: 2018 December 03 21:20:39 »
Ah, I didn't realise you could do that! Muchas Gracias!

4
General / Re: Non-linear Dark current
« on: 2018 December 03 19:23:59 »
Ah, that's interesting, thanks for posting. At least your graph has the same shape as mine :D

Not sure where the offsets are coming from. I might look at the bias frame data for mine. I used an integration to get an average of all biases, but maybe a single bias may remove the offset better.

Cheers
M

5
General / Re: Non-linear Dark current
« on: 2018 December 03 15:55:35 »
Hey Rick

The second graph is what happens for me when I take a gain setting and run bias and darks of varying lengths, then subtract the bias from the result and divide by the number of seconds I exposed for. IOW, it's the number of electrons per second.

Maybe I'm confused, but I would have assumed that given the dark current is supposed to be linear in nature, the number of electrons *per second* should be the same no matter the length of the exposure (as long as the gain stays the same).

So, at say, 135, the number of electrons *per second* varies between 0.031 and 0.008.

The rate at which the dark current accumulates is almost 4 times greater for a 30 second shot, as opposed to a 10 minute shot.

Also, I think I've been using the terms 'dark current' and 'dark noise' interchangeably. Sounds to me like you're saying the dark current *causes the dark noise at a level which is the square root of the dark current. Just trying to get my terms correct :-)

Cheers,

Markus

6
General / Re: Non-linear Dark current
« on: 2018 December 02 19:12:49 »
Dear Markus,

Hi - I measured my dark current for this camera recently as well.

What is a little odd is that there appears to be amp glow when reading an image, but not in the bias frames (not sure why).

So my dark current (as measured by difference between bias frame and dark frame), scaled as a constant plus a linear term. The linear term was very close to that reported by ASI on their web site.

Not sure why your's is exponential. Could you post your results as a graph?

Colin

Sure. Maybe I'm reading things wrong.

Here's the only linear graph I get - when I look at total mean dark current for the entire exposure.

But when I look at the noise in terms of e-/sec you see the non-linear aspect of things.

The first graph shows you that dark current increases over time.

The second tells you that the rate of increase is not linear.

That's what I'm confused about.

Oh, I should point out, all graphs in 12 bit numbers because it relates to the camera better.

Also my 'strange' gain settings are because I wanted the driver gain settings to reflect e-/ADU conversions.

My Unity Gain sits at 135 (not 139 as specified) which is exactly twice the gain of 195 (the first being 1e-/ADU, the second being 0.5 e-/ADU). That way I'm working with actual stops of light, which makes a lot more sense to me.

Cheers, Markus




7
General / Re: Averaging integration doesn't...uh, average
« on: 2018 December 02 18:19:38 »
I'm looking into the noise characteristics of my camera.

Some of those measurements differ by quite small amounts.

I guess I'm after the most accurate data I can get, but in terms of practical day-to-day use it doesn't matter too much, no.

So if I read this right, the integration will be more accurate (and to more decimal places) than the statistics panel?

Cheers

Markus

8
General / Averaging integration doesn't...uh, average
« on: 2018 December 02 02:27:55 »
Take 4 dark frames.

12 bit mean values as follows;

51.47
51.47
51.47
51.46

Average them and you get 51.4675, right?

But, if you take those frames and integrate them using averaging, no noise evaluation, no weighting and no pixel rejection, you get;

Average 51.4682 (and Median gives you 51.4353).

Which is 0.007 higher than a straight up mathematical averaging.

I wonder what's going on?

Is the 'statistics' proccess limited in it's reporting, or is something funky happening during integration?

Anyone know?

Cheers

Markus

9
General / Re: Non-linear Dark current
« on: 2018 November 26 22:05:33 »
Thanks Rob, that's good to know

Best,

Markus

10
General / Non-linear Dark current
« on: 2018 November 26 18:41:43 »
Hey all, I've been following Craig Stark's tutorial on defining your camera's noise characteristics.

According to him, Dark Current should show a linear regression.

I notice my dark current over time increases in a non-linear fashion, more inline with a power series (y=ax^b rather than y=ab^x).

I'm assuming that the dark current scaling algorithm in Pixinsight expects a linear regression (twice as much time = twice as much dark current), so for me the scaling won't work.

I guess I could just take dark flats, but I'd ultimately like to figure out why this is so.

Someone suggested amp-glow may account for this non-linearity.

It could also be an issue with my bias frames which are required for this calculation, but I can't think what. As far as I can tell, the bias and resultant integrated master are fine. Just to be sure, I took the bias series at the same settings as the darks (except for exposure length, of course!)

ASI1600MM Pro, Filterwheel plugged through cameras onboard hub.
Slowest download speed (40). Cable from 1600 going direct to computer
Set point -15 C
It seems a consistent curve shape at exposures ranging from 30 to 600 secs at all gain levels.

Many thanks for any help.

Markus

Pages: [1]