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arXiv · 0712.4140

Bayesian Image Reconstruction Based on Voronoi Diagrams

G. F. Cabrera·S. Casassus·N. Hitschfeld
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Abstract

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.

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BibTeXRIS

G. F. Cabrera, S. Casassus, N. Hitschfeld. 2007-12-26. Bayesian Image Reconstruction Based on Voronoi Diagrams. https://doi.org/10.1086/523961

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