Abstract
Motion deblurring problems are considered, however, as additional difficulty we consider that the motion occurs in front of a still background. First we propose a model for the formation of this kind of partly blurred images which involve four unknown quantities: The object, the background, the blur kernel and a mask that encodes the shape of the object. Then we propose variational methods to solve the deblurring problem. We show that the method performs well if three of the sought-after quantities are known. Finally we show that the method even works for real world examples as soon as the user makes a crude selection of the blurred region in the image.
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Laue, E., Lorenz, D.A. (2013). Variational Methods for Motion Deblurring with Still Background. In: Kuijper, A., Bredies, K., Pock, T., Bischof, H. (eds) Scale Space and Variational Methods in Computer Vision. SSVM 2013. Lecture Notes in Computer Science, vol 7893. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38267-3_7
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DOI: https://doi.org/10.1007/978-3-642-38267-3_7
Publisher Name: Springer, Berlin, Heidelberg
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