Reduction of boundary effects in multiple image deconvolution with an application to LBT LINC-NIRVANA
Our approach proposed in a previous paper for the reduction of boundary effects in the deconvolution of astronomical images by the Richardson-Lucy method (RLM) is extended here to the problem of multiple image deconvolution and applied to the reconstruction of the images of LINC-NIRVANA, the German-...
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Veröffentlicht in: | Astronomy and astrophysics (Berlin) 2006-03, Vol.448 (3), p.1217-1224 |
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container_title | Astronomy and astrophysics (Berlin) |
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creator | ANCONELLI, B BERTERO, M BOCCACCI, P CARBILLET, M LANTERI, H |
description | Our approach proposed in a previous paper for the reduction of boundary effects in the deconvolution of astronomical images by the Richardson-Lucy method (RLM) is extended here to the problem of multiple image deconvolution and applied to the reconstruction of the images of LINC-NIRVANA, the German-Italian beam combiner for the Large Binocular Telescope (LBT). We investigate the multiple image RLM, its accelerated version ordered subsets expectation maximization (OSEM), and the regularized versions of these two methods. In addition we show how the approach can be extended to the iterative space reconstruction algorithm (ISRA), which is an iterative method converging to non-negative least squares solutions. Numerical simulations indicate that the approach can provide excellent results with a considerable reduction of the boundary effects. |
doi_str_mv | 10.1051/0004-6361:20053848 |
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We investigate the multiple image RLM, its accelerated version ordered subsets expectation maximization (OSEM), and the regularized versions of these two methods. In addition we show how the approach can be extended to the iterative space reconstruction algorithm (ISRA), which is an iterative method converging to non-negative least squares solutions. 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We investigate the multiple image RLM, its accelerated version ordered subsets expectation maximization (OSEM), and the regularized versions of these two methods. In addition we show how the approach can be extended to the iterative space reconstruction algorithm (ISRA), which is an iterative method converging to non-negative least squares solutions. 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subjects | Astronomy Earth, ocean, space Exact sciences and technology |
title | Reduction of boundary effects in multiple image deconvolution with an application to LBT LINC-NIRVANA |
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