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- W1699515474 abstract "2D Kalman filtering for the restoration of stochastically blurred images is developed. Stochastic blur is treated as the combination of a deterministic blur and correlated random noise. For restoration from single-frame data, an augmented state-vector Kalman filter for stochastic blurs is derived. This filtering scheme is then extended to provide restoration from multiple-frame data also. Kalman filtering for both serial and parallel processing of the frames is proposed. The new filters can take into account the spatio-temporal correlations of the randomly varying blur. For the equivalent 1-D problem, the proposed filters are the best linear estimators for minimizing the mean-square error over the blur process ensemble and observation noise ensemble. Sample results are also provided to show the effectiveness of the proposed filters. >" @default.
- W1699515474 created "2016-06-24" @default.
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- W1699515474 date "2003-01-06" @default.
- W1699515474 modified "2023-09-27" @default.
- W1699515474 title "2-D Kalman filtering for the restoration of stochastically blurred images" @default.
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- W1699515474 doi "https://doi.org/10.1109/icassp.1988.196767" @default.
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