Malcolm,
Thanks for the thorough reply.
>First a caveat: ESP has not been supported for a good many years.
Is there any other (Starlink) piece of software recommended for this job? Too many times I have found myself in the same situation of having to analyze what I see "by eye" are reasonably good matches for ellipses. Then I begin browsing the Starlink apps and end up trying to make ESP work again and again. Now I wonder whether perhaps I have been choosing the wrong tool...
Regarding my problem: Eventually I found that ELLFOU was able to do what I wanted. However, my isophotes were roughly ~55 pixels in radius and, try as I may, I couldn't persuade it to fit something larger that ~50 pixels in radius. I relaxed all the parameters that according to the documentation would make the program stop but it just didn't do it. I tried this in GAIA and from the command line with the same result. In GAIA I could see the right series of ellipses being fitted inside the much larger region I had defined (I also tried with smaller regions, with the same result). Perhaps there's a hardcoded limit?
Juts FYI I'd like to comment that I tried a different approach to my problem, which may help somebody else: I decided to try image segmentation using PDL::Image2D. Basically I set a series of thresholds which allow me to produce different cuts of the image at that level of counts. The interesting bit is that all the regions with connected series of pixels are set to a common value, so the value in a pixel (say, N) now reports that the pixel belongs to the closed region N in the cut. Thus, after a couple of lines of algebraic manipulation I can get an image in which only one closed region survives. This region can be centroided in PDL (or you can detect the edge and fit ellipses if you want) and that's it. The solution proved to be very robust because the closed region can be identified starting from any pixel inside the region and not only from a reasonable estimate of the centroid. The latter is important for me as I have been trying to deal with very poorly tracked and defocused images, so the centroids can have very obvious jumps between images.
Cheers,
Eduardo
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