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Multiple-frame Image Super Resolution Based on Optic Flow


Mahmoud,  Dina
International Max Planck Research School, MPI for Informatics, Max Planck Society;

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Mahmoud, D. (2011). Multiple-frame Image Super Resolution Based on Optic Flow. Master Thesis, Universität des Saarlandes, Saarbrücken.

Super resolution is the task of reconstructing one or several high resolution images, from one or several low resolution images. A variety of super resolution methods have been proposed over the past three decades, some following a singleframe based methodology while the others utilizing a multiple-frame based one. These methods are usually very sensitive to their underlying model of data and noise, which limits their performance. In this thesis, we propose and compare two multiple-frame based approaches that address such shortcomings. In the rst proposal we investigate a fast, local approach which combines the low resolution frames via warping and then performs diusion-based inpainting. The second proposal models the image formation process in a variational framework with regularization that is robust to errors in motion and blur estimation. In addition, we introduce a brightness adaptation step which results in images with sharper edges. An accurate estimation of optical ow among the low resolution measurements is a fundamental step towards high quality super resolution for both methods. Experiments conrm the eectiveness of our method on a variety of super resolution benchmark sequences, as well as its superiority in performance to other closely-related methods.