Abstract
Imagine an image sequence whose frames are both blurred and noisy. Three frames of such a sequence is shown in Fig. 13.1 where each frame suffers from focus blur as well as additive white Gaussian noise. Due to blur and noise contamination, the amount of information that a human observer or a machine can extract from this sequence is rather limited. It is therefore desirable to restore this image sequence. By that we mean the estimation of the original sequence from its blurred and noisy rendition. (The original sequence is shown in Fig. 13.2)
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Ozkan, M.K., Sezan, M.I., Erdem, A.T., Tekalpt, A.M. (1993). Multiframe Wiener Restoration of Image Sequences. In: Sezan, M.I., Lagendijk, R.L. (eds) Motion Analysis and Image Sequence Processing. The Springer International Series in Engineering and Computer Science, vol 220. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-3236-1_13
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DOI: https://doi.org/10.1007/978-1-4615-3236-1_13
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