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Variational bayesian super resolution

2019-12-09 21:10

Super resolution results (8x resolution increase) on a real dataset. (a) 40 LR images, and the results of (b) bicubic interpolation, (c) RSR, (d) NLS, (e) ALG1 and (f) ALG2.How can the answer be improved? variational bayesian super resolution

(49) Algorithm 1 Variational Bayesian Super Resolution The quantity can be calculated using (35) as Calculate initial estimates of the HR image, registration parameters, and hyperparameters while convergence criterion is not met do 1.

title Variational bayesian super resolution , abstract In this paper, we address the super resolution (SR) problem from a set of degraded low resolution (LR) images to obtain a high resolution (HR) image. The required probability distributions for the Bayesian modeling of the super resolution problem are formulated in Section 3. The Bayesian analysis and posterior probability approximation to obtain the parameters and the super resolution reconstructed image is performed in Section 4.variational bayesian super resolution Thus, the variational Bayesian method, which can simultaneously estimate the HR image, the motion parameters, and the hyperparameters, has been used to improve the reconstruction quality. However, the existing variational Bayesian approaches cannot adapt to local image features.

Utilizing a Bayesian formulation, we model the unknown HR image, the acquisition process, the motion parameters and the unknown model parameters in a stochastic sense. Employing a variational Bayesian analysis, we develop two novel algorithms which jointly estimate the variational bayesian super resolution Experimental results demonstrate that the proposed approaches are very effective and compare favorably to stateoftheart SR algorithms. Index TermsBayesian methods, parameter estimation, super resolution, total variation, variational methods. Variational Bayesian Super Resolution Abstract: In this paper, we address the super resolution (SR) problem from a set of degraded low resolution (LR) images to obtain a high resolution (HR) image. Accurate estimation of the subpixel motion between the LR images significantly affects the performance of the reconstructed HR image. Variational Bayesian Image SuperResolution with GPU Acceleration Giannis K. Chantas Department of Informatics and Telecommunications, TEI of Larissa, Larissa, Greece We're upgrading the ACM DL, and would like your input. Please sign up to review new features, functionality and page designs.

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