Abstract
In this paper, an approach to super-resolution (SR) reconstruction of multi-images is proposed based on improved Keren registration and a revised regularization method, which is characterized with high performance of edge enhancement and processing efficiency. In order to increase the registration speed, the Keren registration method is improved by partition of original images and parallel registration of each small patch. And then a revised regularization method is employed to resolve the ill-posed problem and perform the edge enhancement simultaneously. The experimental results indicate that the processing efficiency is raised in a large extent, provided the image registration precision is as high as the classical methods. In the SR reconstruction effect, it can outperform other super-resolution methods observably, thus takes more advantages in practical applications.
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Liu, M., Huang, J., Gao, M., Qin, S. (2013). High Performance Super-Resolution Reconstruction of Multiple Images Based on Fast Registration and Edge Enhancement. In: Sun, C., Fang, F., Zhou, ZH., Yang, W., Liu, ZY. (eds) Intelligence Science and Big Data Engineering. IScIDE 2013. Lecture Notes in Computer Science, vol 8261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42057-3_82
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DOI: https://doi.org/10.1007/978-3-642-42057-3_82
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