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- W1980826205 abstract "Relative motion between the camera and the object results in the recording of a motion-blurred image. Under certain idealized conditions, such blurring can be mathematically corrected. We refer to this as ‘motion deblurring’. We start with some idealized assumptions under which the motion deblurring problem is a linear inverse problem with certain positivity constraints; LININPOS problems, for short. Such problems, even in the case of no statistical noise, can be solved using the maximum likelihood/EM approach in the following sense. If they have a solution, the ML/EM iterative method will converge to it; otherwise, it will converge to the nearest approximation of a solution, where ‘nearest’ is interpreted in a likelihood sense or, equivalently, in a Kullback-Leibler information divergence sense. We apply the ML/EM algorithm to such problems and discuss certain special cases, such as motion along linear or circular paths with or without acceleration. The idealized assumptions under which the method is dev..." @default.
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- W1980826205 date "1994-01-01" @default.
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- W1980826205 title "Experiments with maximum likelihood method for image motion deblurring" @default.
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- W1980826205 doi "https://doi.org/10.1080/757582980" @default.
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