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Convergence properties of hybrid blind deconvolution

机译:混合盲解卷积的收敛性

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Abstract: The multi-frame blind deconvolution algorithm is considered for processing astronomical speckle images when only a few frames of data are collected. It has been noted that when the speckle data contains even moderate amounts of shot noise the algorithm often converges to the trivial point solution. The convergence properties of the Knox-Thompson algorithm are well understood, however when only a few frames of data are used, the algorithm often contains false structure referred to as processing artifacts. In this paper we consider penalized blind convolution as a `clean up' for the Knox-Thompson algorithm. The utility of this combination is demonstrated images of the Jovian moon Ganymede taken on a 1.5 meter telescope.!10
机译:摘要:当仅收集少量帧数据时,考虑使用多帧盲反卷积算法处理天文散斑图像。已经注意到,当散斑数据甚至包含适量的散粒噪声时,该算法通常会收敛到平凡的点解。 Knox-Thompson算法的收敛特性众所周知,但是,当仅使用几帧数据时,该算法通常包含称为处理伪像的错误结构。在本文中,我们将罚盲卷积视为Knox-Thompson算法的“清理”。该组合的实用性是在1.5米望远镜上拍摄的木星木卫三(Ganymede)的演示图像!! 10

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