May 18, 2021 · In this paper, we consider a parametric model of the blur and introduce an 1D state-space model to describe the statistical dependence among the ...
In this paper, we propose a Bayesian sampling method, for the identification of parametrized space-varying blurs in the context of calibrated images 1. Our ...
In this paper, we consider a parametric model of the blur and introduce an 1D state-space model to describe the statistical dependence among the neighboring ...
Probabilistic modeling and inference for sequential space-varying blur ...
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In this paper, we propose a Bayesian sampling method, for the identification of parametrized space-varying blurs in the context of calibrated images 1. Our ...
Elvira, "Probabilistic modeling and inference for sequential space-varying blur identification", IEEE Transactions on Computational Imaging, vol. 7, pp. 531 ...
Probabilistic modeling and inference for sequential space-varying blur identification. Y Huang, E Chouzenoux, V Elvira. IEEE Transactions on Computational ...
Blur is caused by a pixel receiving light from multiple scene points, and in many cases, such as object motion, the induced blur varies spatially across the ...
Probabilistic Modeling and Inference for Sequential Space-Varying Blur Identification. Article. Full-text available. May 2021. Yunshi Huang ...
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Our framework accurately captures the behavior of the real motion blur that is encountered using a Time-of-Flight (ToF) sensor. This work uses a probabilistic ...
Elvira, “Probabilistic modeling and inference for sequential space-varying blur identification,” IEEE Trans. Comput. Imag., vol. 7, pp. 531–546, 2021 ...