Simultaneous Multi-Frame Map Super-Resolution Video Enhancement Using Spatlo-Temporal Priors
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چکیده
A simultaneous multi-frame super-resolution video reconstruction procedure, utilizing spatio-temporal smoothness constraints and motion estimator confidence parameters is proposed. The ill-posed inverse problem of reconstructing super-resolved imagery from the low resolution, degraded observations is formulated as a statistical inference problem and a Bayesian, maximum a-posteriori (MAP) approach is utilized for its approximate solution. The inclusion of motion estimator confidence parameters and temporal constraints result in higher quality super-resolution reconstructions with improved robustness to motion estimation errors.
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Simultaneous Multi-frame MAP Super-Resolution Video Enhancement using Spatio-temporal Priors
A simultaneous multi-frame super-resolution video reconstruction procedure, utilizing spatio-temporal smoothness constraints and motion estimator confidence parameters is proposed. The ill-posed inverse problem of reconstructing super-resolved imagery from the low resolution, degraded observations is formulated as a statistical inference problem and a Bayesian, maximum a-posteriori (MAP) approa...
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تاریخ انتشار 1999