Multi-Frame Super-Resolution Image Reconstruction Employing the Novel Estimator L1inv-Norm

In multi-frame Super-Resolution (SR) image reconstruction a single High-Resolution (HR) image is created from a sequence of Low-Resolution (LR) frames. This work considers stochastic regularized multi-frame SR image reconstruction from the data-fidelity point of view. In fact, a novel estimator name...

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Κύριος συγγραφέας: Panagiotopoulou, Antigoni
Άλλοι συγγραφείς: Παναγιωτοπούλου, Αντιγόνη
Μορφή: Conference (paper)
Γλώσσα:English
Έκδοση: 2012
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Διαθέσιμο Online:http://hdl.handle.net/10889/5442
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spelling nemertes-10889-54422022-09-05T13:57:25Z Multi-Frame Super-Resolution Image Reconstruction Employing the Novel Estimator L1inv-Norm Panagiotopoulou, Antigoni Παναγιωτοπούλου, Αντιγόνη Super-resolution Data-fidelity Hybrid form L1 estimator Logarithm ln In multi-frame Super-Resolution (SR) image reconstruction a single High-Resolution (HR) image is created from a sequence of Low-Resolution (LR) frames. This work considers stochastic regularized multi-frame SR image reconstruction from the data-fidelity point of view. In fact, a novel estimator named L1inv-norm is proposed for assuring fidelity to the measured data. This estimator presents the hybrid form of both L1 error norm and logarithm ln. The introduced L1inv-norm is combined with the Bilateral Total Variation (BTV) regularization. The proposed SR method is directly compared with an existing SR method which employs the Lorentzian estimator in combination with the BTV regularizer. The experimental results prove that the proposed technique predominates over the existing technique. 2012-09-17T06:09:53Z 2012-09-17T06:09:53Z 11-13 April 2012 2012-09-17 Conference (paper) http://hdl.handle.net/10889/5442 en 19th International Conference on Systems, Signals and Image Processing (IWSSIP), 2012 application/pdf
institution UPatras
collection Nemertes
language English
topic Super-resolution
Data-fidelity
Hybrid form
L1 estimator
Logarithm ln
spellingShingle Super-resolution
Data-fidelity
Hybrid form
L1 estimator
Logarithm ln
Panagiotopoulou, Antigoni
Multi-Frame Super-Resolution Image Reconstruction Employing the Novel Estimator L1inv-Norm
description In multi-frame Super-Resolution (SR) image reconstruction a single High-Resolution (HR) image is created from a sequence of Low-Resolution (LR) frames. This work considers stochastic regularized multi-frame SR image reconstruction from the data-fidelity point of view. In fact, a novel estimator named L1inv-norm is proposed for assuring fidelity to the measured data. This estimator presents the hybrid form of both L1 error norm and logarithm ln. The introduced L1inv-norm is combined with the Bilateral Total Variation (BTV) regularization. The proposed SR method is directly compared with an existing SR method which employs the Lorentzian estimator in combination with the BTV regularizer. The experimental results prove that the proposed technique predominates over the existing technique.
author2 Παναγιωτοπούλου, Αντιγόνη
author_facet Παναγιωτοπούλου, Αντιγόνη
Panagiotopoulou, Antigoni
format Conference (paper)
author Panagiotopoulou, Antigoni
author_sort Panagiotopoulou, Antigoni
title Multi-Frame Super-Resolution Image Reconstruction Employing the Novel Estimator L1inv-Norm
title_short Multi-Frame Super-Resolution Image Reconstruction Employing the Novel Estimator L1inv-Norm
title_full Multi-Frame Super-Resolution Image Reconstruction Employing the Novel Estimator L1inv-Norm
title_fullStr Multi-Frame Super-Resolution Image Reconstruction Employing the Novel Estimator L1inv-Norm
title_full_unstemmed Multi-Frame Super-Resolution Image Reconstruction Employing the Novel Estimator L1inv-Norm
title_sort multi-frame super-resolution image reconstruction employing the novel estimator l1inv-norm
publishDate 2012
url http://hdl.handle.net/10889/5442
work_keys_str_mv AT panagiotopoulouantigoni multiframesuperresolutionimagereconstructionemployingthenovelestimatorl1invnorm
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