Please use this identifier to cite or link to this item: http://hdl.handle.net/10889/5442
Title: Multi-Frame Super-Resolution Image Reconstruction Employing the Novel Estimator L1inv-Norm
Authors: Panagiotopoulou, Antigoni
Issue Date: 2012-09-17
Keywords: Super-resolution
Data-fidelity
Hybrid form
L1 estimator
Logarithm ln
Event: International Conference on Systems, Signals and Image Processing, IWSSIP 2012
Abstract: 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.
Appears in Collections:Τμήμα Φυσικής (Δημοσ. Π.Π. σε συνέδρια)

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