Ground-based image reduction in support of Juno |
Ground-based image reduction in support of Juno |
Dec 9 2016, 04:09 PM
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#1
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Newbie Group: Members Posts: 7 Joined: 9-December 16 From: University of Leicester Member No.: 8085 |
Hello everyone,
I am a postgraduate researcher studying the climate variability of Jupiter during the Juno mission. This involves analysis and comparison of ground-based observations taken from the Very Large Telescope (VLT) in Chile and data, to be used at a later date, from Juno, with ground-based observations corresponding with perijoves of the spacecraft. My first project has been working on reducing images taken by the VISIR mid-infrared instrument (operating range between 5 and 20 microns) on the VLT (more details found below). As a result of new AQUARIUS detector (installed 2016) on VISIR, there is a pattern that plagues all of the images. This pattern causes problems with data retrieval (getting useful information about temperature and composition of the atmosphere) and is also not very nice aesthetically and not entirely suitable for publication. The current technique for reducing this data and removing the lines works fine aesthetically, however it uses the program GiMP. This means that although it fixes the problem, it does so by smoothing or in-painting in ways that aren't truly scientific. Pixel values will be changed and information will be introduced or lost such that it actually affects the science output from the observations. I have provided the link to a public google drive folder containing some of the raw images as a sample of what we are dealing with, I can provide more if necessary. From my (limited) knowledge of programming (Python and IDL) I have been able to remove the central horizontal stripe, but the vertical stripes remain (although the images attached do not show this as they are purely raw images directly from the observatory). If anyone has experience with removing detector patterns and any pattern like this or can recommend some techniques to try it would be greatly appreciated! ESO - VISIR instrument: http://www.eso.org/sci/facilities/paranal/...ents/visir.html Google drive folder: https://drive.google.com/open?id=0B8_Ynti1o...M3hjS3dWal83X28 edit: fixed the links -------------------------------------------------------------------------------------------------- Thank you, Padraig Donnelly DISCLAIMER: All images provided are taken from the VLT in Chile and are fully credited to the European Southern Observatory (ESO). |
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Dec 9 2016, 06:04 PM
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#2
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Senior Member Group: Members Posts: 2542 Joined: 13-September 05 Member No.: 497 |
If anyone has experience with removing detector patterns... Do you have any flat fields? Is this a fixed pattern? If it is fixed, then this is detector 101 stuff. If it's not fixed, then your electronics is broken -------------------- Disclaimer: This post is based on public information only. Any opinions are my own.
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Dec 9 2016, 08:37 PM
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#3
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Newbie Group: Members Posts: 7 Joined: 9-December 16 From: University of Leicester Member No.: 8085 |
Do you have any flat fields? Is this a fixed pattern? If it is fixed, then this is detector 101 stuff. If it's not fixed, then your electronics is broken Yes it is fixed and I am working on getting the flat fields. Also it's the 'detector 101' stuff that I want to know! |
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Dec 10 2016, 05:41 AM
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#4
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Senior Member Group: Members Posts: 2542 Joined: 13-September 05 Member No.: 497 |
Also it's the 'detector 101' stuff that I want to know! It would surprise me if there wasn't a local expert at VLT who has tools to deal with the specifics of this instrument. For IR cameras, if you have a flat field at one scene temperature you can just subtract that from all scenes -- so-called "one point correction". If you have two flats at two different scene temps, you can produce a multiplicative correction by taking the ratio of the two flats and an subtractive correction with the colder flat ("two-point correction"). Usually individual bad pixels have to be mapped and then interpolated over, although running a 3x3 median filter over the image can often be good enough. -------------------- Disclaimer: This post is based on public information only. Any opinions are my own.
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