Like many astronomical missions and data sets, the NASA Kepler satellite imaging is crowded; there is no part of the imaging that contains reliably isolated stars. For this reason, it is hard to infer (from the data) the point-spread function of the instrument simply; any PSF inference requires modeling the images as a crowded image of many overlapping stars (of unknown brightnesses and positions). However, when a star is subject to a planetary or stellar transit, the change in the scene during the transit should be modeled well as a PSF-shaped deficit. So we should be able to infer the PSF from these deficits. The transits are rare, so they rarely overlap. They are also very faint (low-amplitude) events, but (a) the eclipsing-binary stellar transits are not so faint (and very common), and (b) Kepler has good signal-to-noise even on planetary transits.
2012-09-10
de-blur long exposures that show the rotation of the sky
Here at Astrometry.net headquarters we get a lot of images of the night sky where the exposure is long and the stars have trailed into partial circular arcs. If we could de-blur
these into images of the sky, this would be great: Every one of these trailed images would provide a photometric measurement of every star. Advanced goal: Every one of these trailed images would provide a photometric light curve of every star. That would be sweet! Not sure if this is really research, but it would be cool.
The problem is easy, because every star traverses the same angle in a circle with the same center. Easy! But the problem is hard because the images are generally taken with cameras that have substantial field distortions (distortions in the focal plane away from a pure tangent-plane projection of the sky). Still, it seems totally do-able!
Pedants beware: Of course I know that it is the Earth rotating and not the sky rotating! But yes, I have made that pedantic point on occasion too.
2012-08-31
learn distortion models for common cameras
Our astronomical image-recognition software Astrometry.net (see Lang et al 2010) does a very good job on professional-grade astronomical images. It is less reliable on snapshots taken with normal, wide-angle lenses and fish-eye lenses. This is ironic, because from an information-theory point of view, they are much easier to recognize: They contain obvious, familiar constellations. The problem is that these wide-field shots have substantial geometric distortions in the field. These distortions foil Astrometry.net because they make the mapping from sky to focal plane non-conformal (squares on the sky don't go to squares on the image)
Another ironic thing about all this is that in fact these distortions are very common among cameras and very predictable. They should be extremely predictable using the EXIF meta-data in image headers, and even without that I bet the distortions live in a small family of possible choices. The project is: Find out what these standard distortions are, and fix Astrometry.net so it knows about them in advance, either by de-distorting the star list that it eats (this would be the easy option) or else by making the star-figure-matching step invariant to those kinds of distortions (that would be the hard option). Actually even easier would be to just have Astrometry.net automatically lower its tolerances as the asterisms get close to the field edges!