Astronomy and Astrophysics – Astrophysics
Scientific paper
2007-12-26
Astronomy and Astrophysics
Astrophysics
27 pages, 10 figures, to be published in APJ, 672, 1272
Scientific paper
10.1086/523961
We present a Bayesian Voronoi image reconstruction technique (VIR) for interferometric data. Bayesian analysis applied to the inverse problem allows us to derive the a-posteriori probability of a novel parameterization of interferometric images. We use a variable Voronoi diagram as our model in place of the usual fixed pixel grid. A quantization of the intensity field allows us to calculate the likelihood function and a-priori probabilities. The Voronoi image is optimized including the number of polygons as free parameters. We apply our algorithm to deconvolve simulated interferometric data. Residuals, restored images and chi^2 values are used to compare our reconstructions with fixed grid models. VIR has the advantage of modeling the image with few parameters, obtaining a better image from a Bayesian point of view.
Cabrera G. F.
Casassus Simon
Hitschfeld Nancy
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