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- W1618006802 abstract "Obtaining high resolution images of space objects from ground based telescopes involves using a combination of sophisticated hardware and computational post processing techniques. An important, and often highly effective, computational post processing tool is multi-frame blind deconvolution (MFBD) for image restoration. One difficulty with using MFBD algorithms is that the nonlinear inverse problem they are designed to solve may have many local minima. Standard optimization methods that use the gradient to search for a minimum may get trapped in a local minimum, resulting in a less than optimal restored image. Moreover, in some cases the global minimum may not correspond to the best reconstructed image compared to a different local minimum. In this paper we consider a flexible optimization approach that can easily incorporate various filtering schemes and prior information, resulting in a scheme that is computationally more tractable. Practical implementation details are discussed." @default.
- W1618006802 created "2016-06-24" @default.
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- W1618006802 date "2009-01-01" @default.
- W1618006802 modified "2023-09-23" @default.
- W1618006802 title "MFBD and the Local Minimum Trap" @default.
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