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Proceedings Paper

Joint image registration and reconstruction from compressed multi-view measurements
Author(s): Gilles Puy; Pierre Vandergheynst
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Paper Abstract

We present a method for joint reconstruction of a set of images representing a given scene from few multi-view measurements obtained by compressed sensing. We model the correlation between measurements using global geometric transformations represented by few parameters. Then, we propose an algorithm able to jointly estimate these transformation parameters and the observed images from the available measurements. This method is also robust to occlusions appearing in the scene. The reconstruction algorithm minimizes a non-convex functional and generates a sequence of estimates converging to a critical point of this functional. Finally, we demonstrate the efficiency of the proposed method using numerical simulations.

Paper Details

Date Published: 26 September 2013
PDF: 8 pages
Proc. SPIE 8858, Wavelets and Sparsity XV, 88580Z (26 September 2013); doi: 10.1117/12.2023916
Show Author Affiliations
Gilles Puy, Ecole Polytechnique Fédérale de Lausanne (Switzerland)
Pierre Vandergheynst, Ecole Polytechnique Fédérale de Lausanne (Switzerland)

Published in SPIE Proceedings Vol. 8858:
Wavelets and Sparsity XV
Dimitri Van De Ville; Vivek K. Goyal; Manos Papadakis, Editor(s)

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