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Reconstruction of Images with Poisson Noise

Sylwester J., Sylwester B.

Acta Astronomica

1999

Vol. 49, No. 2

189--199

This paper addresses quantitatively the problem of influence of statistical uncertainties embedded in the recorded image on uncertainties of the reconstructed image. In the analysis we use iterative maximum likelihood algorithm Andril (described by Sylwester and Sylwester 1998) developed for massive deconvolution of flare images obtained by the Soft X-ray Telescope (SXT) on Yohkoh. We illustrate the "ill-conditioned" nature of the image reconstruction problem and suggest the ways to reduce, at least partly, propagation of noise to the reconstructed image.

ANDRIL - Maximum Likelihood Algorithm for Deconvolution of SXT Images

Sylwester J., Sylwester B.

Acta Astronomica

1998

Vol. 48, No. 3

519--545

We present an iterative deconvolution algorithm called ANDRIL devoted for advanced processing of images obtained by the Soft X-ray Telescope (SXT) on Yohkoh. The algorithm is based on maximum likelihood approach. We introduced several modifications to this algorithm in order to optimize its properties. The goal of the algorithm is to remove numerically the image blurring due to the instrument point spread function (PSF) and increase the image resolution. The application of the algorithm allows to resolve soft X-ray structures in the SXT images on the angular scales down to 1 arcsec. Presented algorithm has been recently used for analysis of detailed morphology and physical conditions in the plasma of flaring structures.