A closed form algorithm for superresolution

Authors:
Marcelo O. Camponez;Evandro O. T. Salles;Mário Sarcinelli-Filho
Affiliations:
Graduate Program on Electrical Engineering, Federal University of Espirito Santo, Vitória, ES, Brazil;Graduate Program on Electrical Engineering, Federal University of Espirito Santo, Vitória, ES, Brazil;Graduate Program on Electrical Engineering, Federal University of Espirito Santo, Vitória, ES, Brazil
Venue:
ISVC'11 Proceedings of the 7th international conference on Advances in visual computing - Volume Part II
Year:
2011

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Abstract

Superresolution is a term used to describe the generation of high-resolution images from a sequence of low-resolution images. In this paper an algorithm proposed in 2010, which gets superresolution images through Bayeasian approximate inference using a Markov chain Monte Carlo (MCMC) method, is revised. From the original equations, a closed form to calculate the high resolution image is derived, and a new algorithm is thus proposed. Several simulations, from which two results are here presented, show that the proposed algorithm performs better, in comparison with other superresolution algorithms.