PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Online Blind Deconvolution for Astronomy
Stefan Harmeling, Suvrit Sra, M. Hirsch and Bernhard Schölkopf
In: ICCP 2009, San Francisco(2009).

Abstract

Atmospheric turbulences blur astronomical images taken by earth-based telescopes. Taking many short-time exposures in such a situation provides noisy images of the same object, where each noisy image has a different blur. Commonly astronomers apply a technique called ``Lucky Imaging'' that selects a few of the recorded frames that fulfill certain criteria, such as reaching a certain peak intensity (``Strehl ratio''). The selected frames are then averaged to obtain a better image. In this paper we introduce and analyze a new method that exploits all the frames and generates an improved image in an online fashion. Our initial experiments with controlled artificial data and real-world astronomical datasets yields promising results.

EPrint Type:Conference or Workshop Item (Oral)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
Learning/Statistics & Optimisation
ID Code:4956
Deposited By:Suvrit Sra
Deposited On:24 March 2009