Luminous Landscape Forum
Equipment & Techniques => Digital Cameras & Shooting Techniques => Topic started by: Emmett on January 08, 2018, 02:48:06 pm
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It's been a while since I have been looking for variables that is measured for sensor characterisation and benchmarking. There are some literatures out on the net and yet I cannot figure out which ones can be most important. I am also looking for independant sensor properties, for example FWC and sensor pitch are (to my knowledge) independent variables that will influence the sensor response/capabilities in different lighting scenarios. I appreciate if someone could introduce me a source or provide me the answer.
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In my humble estimation, the resources provided by Roger Clark (www.clarkvision.com) are the best I've encountered.
He is very bright...deeply informed...and committed.
See what you think.
Cheers....
Hank
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In my humble estimation, the resources provided by Roger Clark (www.clarkvision.com) are the best I've encountered.
bclaff @ http://www.photonstophotos.net
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It's been a while since I have been looking for variables that is measured for sensor characterisation and benchmarking.
if you are a technical vs just a reader = Albert Theuwissen's blog @ http://harvestimaging.com/blog/
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Thanks Hank and DP for your reply. :)
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In my humble estimation, the resources provided by Roger Clark (www.clarkvision.com) are the best I've encountered.
+1 to that. He has a big tabulated list of sensors on one of his page; only thing being that it is not up to date as in the sensors are all about 10+ years.
For example Foveon F7 (Sigma SD10) but nothing later, e.g. Merrill.
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bclaff @ http://www.photonstophotos.net
Thanks, yes, I have recently used his Heatmap data for sensor comparison, you may like to have a look:
https://multianalytics.blog/multivariate-analysis-on-sensor-classification-and-variability/
https://multianalytics.blog/2018/03/03/complementary-figures-for-canon-nikon-and-sony/
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It's been a while since I have been looking for variables that is measured for sensor characterisation and benchmarking. There are some literatures out on the net and yet I cannot figure out which ones can be most important. I am also looking for independant sensor properties, for example FWC and sensor pitch are (to my knowledge) independent variables that will influence the sensor response/capabilities in different lighting scenarios. I appreciate if someone could introduce me a source or provide me the answer.
If you want to invest some time and are fairly technical, this is pretty comprehensive:
https://amazon.com/Photon-Transfer-Press-Monograph-PM170/dp/0819467227/ref=sr_1_1?ie=UTF8&qid=1520114919&sr=8-1&keywords=photon+transfer+spie
It emphasizes the measurement of sensors.
In practice, FWC and pitch are not independent variables.
Jim
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If you want to invest some time and are fairly technical, this is pretty comprehensive:
https://amazon.com/Photon-Transfer-Press-Monograph-PM170/dp/0819467227/ref=sr_1_1?ie=UTF8&qid=1520114919&sr=8-1&keywords=photon+transfer+spie
It emphasizes the measurement of sensors.
In practice, FWC and are not independent variables.
Jim
Thanks Jim for the link. Maybe I haven't put it clearly. I would wanted to know if there are other attributes that I can collect their data and are affected by other variables, for example sensor size, FWC or Pitch are physical characteristics of a sensor and do not vary during photon acquisition.
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Thanks Jim for the link. Maybe I haven't put it clearly. I would wanted to know if there are other attributes that I can collect their data and are affected by other variables, for example sensor size, FWC or Pitch are physical characteristics of a sensor and do not vary during photon acquisition.
RN, PRNU, QE?
In DR-Pix sensors, RN is a strong non-monotonic function of ISO setting.
You could break down RN into frame-to-frame invariant and variable components if you can get data.
I believe in modern sensors, PRNU is negligible.
Jim
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RN, PRNU, QE?
In DR-Pix sensors, RN is a strong non-monotonic function of ISO setting.
You could break down RN into frame-to-frame invariant and variable components if you can get data.
I believe in modern sensors, PRNU is negligible.
Jim
Is background noise an intrinsic characteristics of a photon detector?
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Is background noise an intrinsic characteristics of a photon detector?
You mean dark-field noise? There are other sources than the photodiode itself, and they are usually larger. I don't know any way to measure the noise of the photodiode itself. I'm sure it can be modeled, though.
https://www.thorlabs.com/images/TabImages/Photodetector_Lab.pdf
https://www.rp-photonics.com/spotlight_2009_12_13.html
https://www.st-andrews.ac.uk/~ctab/MSc_Oft/Lecture_Notes/lecture_10.pdf
http://ecee.colorado.edu/~mcleod/teaching/ugol/lecturenotes/Lecture%209%20Photodetection.pdf
Jim
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sorry to hijack the thread... what Fuji might be doing @ the edges of the sensor (on sensor, post ADC, wherever, etc) near clipping in blue & green channels ? this is Fuji X-H1
raws are (sequence of clipped raws @ all nominal ISO values) = https://www.amazon.com/clouddrive/share/jV7P00eJdyN1exO14BSXNqERj9Iw01kc7mQtz49VVVm
(https://s26.postimg.org/4u8mznxg7/DSCF1182-20180303-172412-_Raw_Digger-_Screen_Shot.png)
see the pattern near borders, like somebody bites into it... red channel is perfectly clipped by firmware
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You mean dark-field noise? There are other sources than the photodiode itself, and they are usually larger. I don't know any way to measure the noise of the photodiode itself. I'm sure it can be modeled, though.
https://www.thorlabs.com/images/TabImages/Photodetector_Lab.pdf
https://www.rp-photonics.com/spotlight_2009_12_13.html
https://www.st-andrews.ac.uk/~ctab/MSc_Oft/Lecture_Notes/lecture_10.pdf
http://ecee.colorado.edu/~mcleod/teaching/ugol/lecturenotes/Lecture%209%20Photodetection.pdf
Jim
Thanks Jim, very helpful indeed. :)