Non-Windows stacking software.

Paul,

If you don’t mind command line software I have written a set of tools which I use as part of my image calibration and processing pipeline. They are based on the cfitsio library so should read any format supported by that library. You can download them  from here:

http://www.nickdjames.com/astrolinux/utils.tgz

The stacking tool is called fcombine. The normal syntax to use it is:

fcombine -N -a 611,713 -A 0 -o 0.368,236.7,1.42 200p_ofs FLI*200P*FITThis says:

Normalise the median level of each image before stacking, track on a guide star at position 611,713 in the first image, PA of the image is 0 deg (i.e. north up), Offset at 0.368 arcsec/sec in PA 236.7 deg, Pixel scale is 1.42 arcsec/pix. Output file is 200p_ofs and the input files are all files which match FLI*200P*FIT. You can add -F to write as a float fits and -s to do a true average rather than a statistically clipped average. You can also use -v to get a lot of stuff about what it is doing during teh stack (otherwise it is silent). Note that the position for the guide star assumes (1,1) is the top left corner of the image (the convention most amateur software uses) rather than the bottom left (which is what pros tend to use). The FITS standard doesn’t say which is right.

Typing the command with no arguments gives a list of what it can do. For fcombine you get:

fcombine [opts] outfile infiles
By default combines images using mean with outlier rejection
-a x,y[,d]      Align on guidestar
-A n[,M]        Position angle of image with optional mirroring
-C      Cometstack
-c n    Crop to image of size nxn
-d n    Resample and drizzle by a factor of n
-F      Write float format rather than int16
-f file Take alignment offsets from file
-g n    Apply gain of n to output
-h      Do not use FITS header
-m      Minimum pixels
-M      Maximum pixels
-n      Normalize mean levels by scaling
-N      Normalize mean levels by offset
-v      Verbose
-V      Version
-r n    Tracking and PSF radius to use (default = 5.0)
-I      Scale to a FITS that IRIS can handle
-R      Write output mirror reversed
-o rate,pa,pix  Offset (arcsec/min)
-O rate,pa,pix  Offset (arcsec/frame)
-p n    Add pedestal of n
-P n    Reject for PSF > n
-D n    Shift step size (default is 1)
-s      No outlier rejection
-S n    Stacksize (all images by default
-t      Align on target


I have aligned fits images using Python, AstroPy and the astroalign package.

If interested email me, and i’ll send a fairly trivial example python script.

Callum

Yes, Python does make it very easy… Not as fast as C of course.

Good try Paul but that’s the trouble with faint objects in busy starfields! When you say it is “in about the right place” could you quantify in terms of arcsec? Leda’s ephemeris will be very good. Normally, in cases like this, you would produce two stacks at different times and check that the object’s motion is consistent with the ephemeris.  You may not have enough subs to do this in which case the identification will always be iffy.

Well, given the position, it is possibly Leda but I don’t think you could be sure unless you had multiple stacks which showed the blob moving at the correct rate. If you try this in future you will want to get a long enough series of subs that you can make two separate stacks, each of which have enough SNR to get astrometry of the object. Once you have confirmed it by its motion you can always stack the whole set to get a higher SNR. That’s what I did with this faint comet which was about the same magnitude as Leda.

https://openphdguiding.org/man-dev/Tools.htm#Comet_Tracking

Although I have never used this myself…