Superresolution restoration of an image sequence: adaptive filtering approach
Superresolution restoration of an image sequence: adaptive filtering approach
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DOI：
10.1109/83.748893
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发表时间：
1999-03
期刊：
影响因子：
--
通讯作者：
Michael Elad;A. Feuer
中科院分区：
文献类型：
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作者：
Michael Elad;A. Feuer
This paper presents a new method based on adaptive filtering theory for superresolution restoration of continuous image sequences. The proposed methodology suggests least squares (LS) estimators which adapt in time, based on adaptive filters, least mean squares (LMS) or recursive least squares (RLS). The adaptation enables the treatment of linear space and time-variant blurring and arbitrary motion, both of them assumed known. The proposed new approach is shown to be of relatively low computational requirements. Simulations demonstrating the superresolution restoration algorithms are presented.
