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Strehl-constrained iterative blind deconvolution for post-adaptive-optics data
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DOI：10.1051/0004-6361/200912913.png)
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摘要
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Aims. We aim to improve blind deconvolution applied to post-adaptive-optics (AO) data by taking into account one of their basic characteristics, resulting from the necessarily partial AO correction: the Strehl ratio. Methods. We apply a Strehl constraint in the framework of iterative blind deconvolution (IBD) of post-AO near-infrared images simulated in a detailed end-to-end manner and considering a case that is as realistic as possible. Results. The results obtained clearly show the advantage of using such a constraint, from the point of view of both performance and stability, especially for poorly AO-corrected data. The proposed algorithm has been implemented in the freely-distributed and CAOS-based Software Package AIRY.
Keyword:
methods: data analysis
methods: numerical
techniques: image processing
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期刊
IF:
5.8
论文数:
5.0W
被引数:
18.3W
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