A sequential Monte Carlo for astronomic imagingPP

Solar flares are sudden flashes of brightness on the surface of the Sun, which can strongly affect satellite operations, aviation and communication technologies. Here, images of solar flares are reconstructed by assuming that the data (registered with a NASA satellite) have been generated by a combination of few simple geometrical objects, whose parameters are estimated with a sequential Bayesian approach. Numerical results show the advantages of this Bayesian method for both synthetic and real data.

This is poster number 34 in Poster Session

Federica Sciacchitano (Dept. Mathematics, University of Genoa)
Alberto Sorrentino (University of Genoa)
Michele Piana (Dept. Mathematics, University of Genoa)
Anna Maria Massone (CNR - SPIN)
astronomic imaging, bayesian methods, inverse problems, statistical inverse estimation methods, stochastic processes