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12 September 2012 Super resolution from diffraction limited images with kernel-phases
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Kernel-phase is a recently developed paradigm to tackle the classical problem of image deconvolution, based on an interferometric point of view of image formation. Kernel-phase inherits and borrows from the notion of closure-phase, especially as it is used in the context of non-redundant Fizeau interferometry, but extends its application to pupils of arbitrary shape, for diffraction limited images. It can therefore readily be (and is being) used to process existing archival data acquired by space borne telescopes (HST/NICMOS) as well as well corrected AO data from ground based telescopes. The additional calibration brought by kernel-phase boosts the resolution of conventional images and enables the detection of otherwise hidden faint features at the resolution limit and beyond, a regime often refered to as super-resolution. Kernel-phase analysis of archival data leads to new discoveries and/or improved relative astrometry and photometry. The paper also presents how the technique may influence the geometry of new interferometric arrays designed for imaging, dusting off a topic that has known little evolution for the past 40 years; and presents hints of a fast solution to the calibration of non-common path errors in AO systems, using direct focal plane based wavefront sensing.
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Frantz Martinache "Super resolution from diffraction limited images with kernel-phases", Proc. SPIE 8445, Optical and Infrared Interferometry III, 844504 (12 September 2012);

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