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Conference Paper

Demosaicing by Smoothing along 1D Features

MPS-Authors
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Ajdin,  Boris
Computer Graphics, MPI for Informatics, Max Planck Society;

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Hullin,  Matthias B.
Computer Graphics, MPI for Informatics, Max Planck Society;
International Max Planck Research School, MPI for Informatics, Max Planck Society;

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Fuchs,  Christian
Computer Graphics, MPI for Informatics, Max Planck Society;

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Seidel,  Hans-Peter       
Computer Graphics, MPI for Informatics, Max Planck Society;

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Lensch,  Hendrik P. A.
Computer Graphics, MPI for Informatics, Max Planck Society;

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Ajdin-2008-DSF.pdf
(Preprint), 11MB

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Citation

Ajdin, B., Hullin, M. B., Fuchs, C., Seidel, H.-P., & Lensch, H. P. A. (2008). Demosaicing by Smoothing along 1D Features. In IEEE Conference on Computer Vision and Pattern Recognition (pp. 2423-2430). Los Alamitos, CA: IEEE Computer Society.


Cite as: https://hdl.handle.net/11858/00-001M-0000-000F-1B65-F
Abstract
Most digital cameras capture color pictures in the form of an image mosaic,
recording only one color channel at each pixel position. Therefore, an
interpolation algorithm needs to be applied to reconstruct the missing color
information. In this paper we present a novel Bayer pattern demosaicing
approach, employing stochastic global optimization performed on a pixel
neighborhood. We are minimizing a newly developed cost function that increases
smoothness along one-dimensional image features. While previous algorithms have
been developed focusing on LDR images only, our optimization scheme and the
underlying cost function are designed to handle both LDR and HDR images,
creating less demosaicing artifacts, compared to previous approaches.