Random, time-varying blur due to atmospheric turbulence is known to significantly limit image quality. In division-of-time polarimeters, turbulence also randomly distorts the images that are used to infer the polarization content of the scene, leading to substantial Stokes image estimation errors. This research proposes a method to jointly estimate the full polarization properties of a scene along with the point spread functions (PSFs) for each imaging channel in the presence of isoplanatic turbulence. In particular, this research significantly expands on an existing algorithm, to include circular polarization in the framework of a generalized expectation maximization approach. The effectiveness of the approach is demonstrated on laboratory data using a surrogate phase screen placed near the entrance pupil of an imaging system.
It is currently possible for space debris to remain undetected in close proximity to satellites. Current detection methods are adept at locating a single object in space, as well as two objects that are greatly separated, but have difficulty finding a second object that is nearby. The problem is exacerbated if the second object appears much dimmer than the first object. The method proposed in this paper would work with existing methods as an additional processing step that would process areas of astronomical images around places where objects are detected. In this case the proposed algorithm is designed to look at a pixel and determine how bright an object would be if there were an object there, then applies a binary hypothesis test to determine if an object is present. In theory, this will have the greatest advantage over existing methods when the objects are very close together or the second object is very dim. The algorithm has been tested on both simulated data and on a laboratory level test and improved the probability of detection by up to 300%.
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