jan.frenzel
New member
Hi everybody.
I am interested in quantifying image noise., and I could need some help.
Just some background information. I am a hobby astronomer (since 1 year) and I use Pixinsight (advanced beginner level). Recently I figured out that I could also use Pixinsight in my job. I am a materials scientist, working at the Ruhr University in Bochum. We do a lot of electron microscopy for microstructure characterization of structural and functional engineering materials. It just turned out that we can use the Pixinsight process very well to improve image quality of electron diffraction images, where we also have often quite poor signal to noise ratios.
In the next months, we will probably write a short publication on using PI for the analysis of electron diffraction pattern. Therefore, I could need some help. I would be very happy to get some feedback on the points listed below:
1) Where can I get more information on noise and noise determination of images? My impression is that noise estimation in general is a quite complex topic (I read some older posts). I know that PI often uses the k-sigma noise estimate. It would be great to read more about this procedure (citable reference?). Our image files do not contain stars. Most parts are dark grey, and there are various lines resulting from electron diffraction. I would like to be sure that this procedure yields reasonable data on noise in our images.
2) Is there a way to perform a noise estimate on an arbitrary image file (e.g. a single file which I just opened)? For me, it seems the these noise estimate values only get reported after an integration process. I also would like to have these data for selected subframes.
3) I know that there seem to be other procedures for noise estimation. For example, there is the signal to noise ratio (SNR) script by Hartmut Bornemann. One can use it to assess the SNR of the currently activated image. However, I do not know how it works. And I also would like to get reasonable quantitative data e.g. on noise in bias images. I guess a signal to noise ratio for bias images does not make sense since there actually should not be a real signal in these bias frames...
4) As a beginner user of PI I do not have a very deep knowledge on the different processes (e.g. integration with scale factors, pixel rejection algorithms, the advantages of using bias-scaled darks, arcsinhyp stretching, etc). I guess that at least some of these processes must have been described in the (citable) literature at some point. Are there any overview books or papers where I can find references?
Ok... so many things....
It would be really great to have some feedback. That would really be helpful.
Thank you very much and best regards
Jan Frenzel
I am interested in quantifying image noise., and I could need some help.
Just some background information. I am a hobby astronomer (since 1 year) and I use Pixinsight (advanced beginner level). Recently I figured out that I could also use Pixinsight in my job. I am a materials scientist, working at the Ruhr University in Bochum. We do a lot of electron microscopy for microstructure characterization of structural and functional engineering materials. It just turned out that we can use the Pixinsight process very well to improve image quality of electron diffraction images, where we also have often quite poor signal to noise ratios.
In the next months, we will probably write a short publication on using PI for the analysis of electron diffraction pattern. Therefore, I could need some help. I would be very happy to get some feedback on the points listed below:
1) Where can I get more information on noise and noise determination of images? My impression is that noise estimation in general is a quite complex topic (I read some older posts). I know that PI often uses the k-sigma noise estimate. It would be great to read more about this procedure (citable reference?). Our image files do not contain stars. Most parts are dark grey, and there are various lines resulting from electron diffraction. I would like to be sure that this procedure yields reasonable data on noise in our images.
2) Is there a way to perform a noise estimate on an arbitrary image file (e.g. a single file which I just opened)? For me, it seems the these noise estimate values only get reported after an integration process. I also would like to have these data for selected subframes.
3) I know that there seem to be other procedures for noise estimation. For example, there is the signal to noise ratio (SNR) script by Hartmut Bornemann. One can use it to assess the SNR of the currently activated image. However, I do not know how it works. And I also would like to get reasonable quantitative data e.g. on noise in bias images. I guess a signal to noise ratio for bias images does not make sense since there actually should not be a real signal in these bias frames...
4) As a beginner user of PI I do not have a very deep knowledge on the different processes (e.g. integration with scale factors, pixel rejection algorithms, the advantages of using bias-scaled darks, arcsinhyp stretching, etc). I guess that at least some of these processes must have been described in the (citable) literature at some point. Are there any overview books or papers where I can find references?
Ok... so many things....
It would be really great to have some feedback. That would really be helpful.
Thank you very much and best regards
Jan Frenzel