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Reconstruction of a High Resolution Image from Multiple Low Resolution Images

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Super-Resolution Imaging

Abstract

In this chapter the problem of reconstructing a high resolution image from multiple aliased and shifted by sub-pixel shifts low resolution images is considered. The low resolution images are possibly degraded by unknown blurs and their sub-pixel shifts are not known. This problem is described in the frequency and spatial domains. Algorithms for providing solutions to it are reviewed. In addition, two approaches are presented in detail for solving this low-to-high resolution problem. In the first of these two approaches registration and restoration is performed simultaneously using the expectation-maximization (EM) algorithm. The high resolution image is then reconstructed using regularized interpolation which is performed as a separate step. For this reason this approach is abbreviated as RR-I which corresponds to registration/restorationinterpolation. In the second of these approaches registration, restoration and interpolation are perfomed simultaneously using the EM algorithm. Therefore this approach is abbreviated as RRI which corresponds to registration/restoration/interpolation. Numerical experiments are presented that demonstrate the effectiveness of the two approaches.

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Tom, B.C., Galatsanos, N.P., Katsaggelos, A.K. (2002). Reconstruction of a High Resolution Image from Multiple Low Resolution Images. In: Chaudhuri, S. (eds) Super-Resolution Imaging. The International Series in Engineering and Computer Science, vol 632. Springer, Boston, MA. https://doi.org/10.1007/0-306-47004-7_4

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  • DOI: https://doi.org/10.1007/0-306-47004-7_4

  • Publisher Name: Springer, Boston, MA

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