I have worked with the EFM method for removing scattered light, testing it on a synthetic moon image from night JD 2455923.
The “true” scattered light is represented by an image:
S_true = observed – pedestal – usethisidealimage
The best guess scattered light is represented by the end result from the fit minus the pedestal:
S_efm = trialim – pedestal
I have investigated the mean value of S in the 3 boxes shown below for 100 S_true and corresponding S_efm images. It is the same synthetic image that is the basis of all the “observed” images, but they have slightly different noise added when they are convolved with the PSF.
The results:
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It is clear that we have significant bias. Not all the stray light is removed with the EFM method. On the positive side, the standard deviations of the fits are small. The counts here can be compared to a typical DS signal of 5 counts.
@ Chris: The images called observed.fits (made by applying the fortran routine syntheticmoon to an ideal image) only have discrete values, and this means that some pisxels on the ES side has dropped to the value of the pedestal, which for this particular image is 100. I don’t know why syntheticmoon only returns discrete values though…
Henritette — I was just wondering about the “black dots” on the ES side of the image inthis posting. It seemst ahtt here are some dropout pixels — where the counts go very low — posibly to zero. I noticed this at one point when witing the code here and tested it yesterday to see if it was still a problem, but the code I am using here doesn’t give these dropouts. Are they dropping all the way to zero counts? – Chris
We should test if the bias is due to convolution – does flux remain conserved in small regions or only in large ones?
Very nice test! Good material for your thesis.