![]() ...
·
![]()
·
2
likes
|
---|
1 hour on f2 ≠ 1 hour on f7 1 hour of 120 30sec exposures ≠ 1 hour of 6 10min exposures 1 hour on OSC ≠ 1 hour on Mono etc… Should we maybe come up with something better than hours? 🙃 |
![]() ...
·
![]() |
---|
Hey Maxim, what is this related to? Perhaps you meant to reply to an existing topic? Looks like you opened a new discussion topic with no references.
|
![]() ...
·
![]()
·
6
likes
|
---|
Maxim: I think I get your point, but I'm not sure there is a good way to solve this. You would also need to somehow factor in bortle scale, sensor sensitivity, moon position and filter bandwidth, and maybe other things. Stating total exposure in hours is probably the best common denominator that makes sense. |
![]() ...
·
![]()
·
7
likes
|
---|
Maxim: No |
![]() ...
·
![]() |
---|
D. Jung: It’s definitely the best to show the effort, but if we imagine the statement “1000h image of M31 taken with f15 refractor”, here I’m automatically skeptical about the relevance of the hours to the final result. That’s why it’d be cool to have some other units, similar to golf handicap or something 😅 but as you said there are probably too many factors to consider |
![]() ...
·
![]()
·
1
like
|
---|
Oh I see the point. I think the issue is that there are too many factors involved, and you couldn't normalize them all. I'd love to see an equation that normalizes hours by all applicable factors ![]() |
![]() ...
·
![]()
·
17
likes
|
---|
On the same topic, I do have further (fun) KPI suggestions:
|
![]() ...
·
![]()
·
2
likes
|
---|
Maxim:D. Jung: Why skeptical of the hours at f15? If you're imaging a given patch of M31, then aperture matters more about the signal of that patch recorded than f ratio. F ratio/focal length for a given aperture just tell you how magnified that given patch is on the sensor. Aperture is a better indication of how many photons from that patch made it to the sensor. What about central obstruction? Light loss through scatter? As D. Jung mentioned, there are many, many factors that go into how many subject photons are captured per image and how much noise (S/N) and at what spatial resolution. |
![]() ...
·
![]()
·
7
likes
|
---|
Maxim: Better than hours for what? Are you trying to compute signal strength? If so, perhaps you should learn more about radiometry. You could then compute the signal strength in Watts/m^2 and then multiply that by the area of your pixel times the responsivity of the sensor in photo-electrons/Watt to arrive at photo-electrons from each sensor, which will of course vary over the field depending on the irradiance distribution of the object. I'm afraid that you'll never get a good answer without first asking a good question. What is it that you are trying to improve? John |
![]() ...
·
![]()
·
1
like
|
---|
Perhaps SNR of the final stacked linear image would be a better metric, however this isn't as commonly understood as "hours" amongst the photography community. However @D. Jungs suggestions are spot on lol
|
![]() ...
·
![]() |
---|
Thanks for all the great answers! I guess the signal strength or SNR is closest. I think I was referring mostly to the hours multiplied by sort of "system potential", so the final unit reflects time, equipment, conditions, rather than SNR of the final image. |
![]() ...
·
![]()
·
1
like
|
---|
Salvatore Iovene: Normalised hours = (actual hours of exposure) x (no. of mosquito bites/location on torso) + (risk of cable snag^2) - (cloudiness% x 42) - (Windows update timing x 6.02 x 10^23) A normal session for me. |
![]() ...
·
![]()
·
2
likes
|
---|
If you want to compare photons to photons with some account for sky noise between setups for broadband images, it can be approximated by the following: S - Score p = pixel size in microns F = F ratio T = total integration time SQM = sky brightness in (magnitude / arcseonds^2) assuming a limit of 22. S = (p/F)^2 * T * 2.512^(22-SQM) Aiming for a score of 1 should provide a relatively noise-free image if not stretched over aggressively. For dark nebula with high contrast 2+, and for faint tenuous IFN, 5+. This assumes that between setups the same QE (quantum efficiency), filter bandwidth and transmission, and optical transmission/reflectivity. Astrobin can have all of this data if someone provides all of the gear they used, as well as an SQM estimate. SQM could also be approximated by Bortle and average moon % as well. To account for mono LRGB imaging you could use the luminance as the base integration time + a synthetic luminance integration time. Maybe the following: T_eff = effective integration time T_lum = luminance integration time T_R = Red filter integration time T_G = Green filter integration time T_B = Blue filter integration time T_eff = T_lum + (T_R + T_G + T_B)/3 An idea for color richness: If you care about color richness you could use (T_R + T_G + T_B)/3 for integration time, and for color cameras it would just be (T / 1.2). I'm using 1.2 as an approximation for the Bayer matrix channel spillover (i.e. where the red filter picks up some 'blue light' or the blue filter picks up some 'red light'). Mono imaging with RGB filters with distinct cutoffs provides more color distinction and richness over a color camera. Narrowband: If someone can think of a way to include how narrowband can improve contrast and boost the score as a term I'm all ears. My initial attempts at that seem incredibly complicated since the QE profile of cameras, the spectrum of the sky, the filter bandwidth, and the f-ratio of the system need to be taken into account. |
![]() ...
·
![]()
·
1
like
|
---|
Another way to ask the OP's question, why is such a subjective and arbitrary metric so commonly used as a fundamental measure of our images? Which then begs the question, what else? I agree whether it's exposure time, total integration time, aperture, focal ratio, etc. it all leads to SNR, but how to objectively calculate SNR if you're not JH?….. : ) Cheers, Scott |
![]() ...
·
![]() |
---|
D. Jung: Indeed. If we take into account the capital costs of equipment (Astro gear, PC, software etc.) and even such things as travel expenses (car/flights, accommodation etc.), perhaps the most alarming KPI would be "Average Cost per Final Image". But of course it must stand against "Personal Sense of Fulfilment per Final Image". ![]() Cheers. |