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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Marim, M.M. Atlan, M. Angelini, E.D. Olivo-Marin, J.-C. |
| Copyright Year | 2010 |
| Description | Author affiliation: Institut Langevin. ESPCI ParisTech - CNRS UMR 7587, INSERM U 979, UPMC, UP7. F-75005, France (Atlan, M.) || Institut Pasteur, Unité d'Analyse d'Images Quantitative CNRS URA 2582, F-75015 Paris, France (Marim, M.M.; Olivo-Marin, J.-C.) || Institut Télécom, Télécom ParisTech CNRS LTCI, F-75013, France (Angelini, E.D.) |
| Abstract | This paper describes an original microscopy imaging framework successfully employing Compressed Sensing for digital holography. Our approach combines a sparsity minimization algorithm to reconstruct the image and digital holography to perform quadrature-resolved random measurements of an optical field in a diffraction plane. Compressed Sensing is a recent theory establishing that near-exact recovery of an unknown sparse signal is possible from a small number of non-structured measurements. We demonstrate with practical experiments on holographic microscopy images of cerebral blood flow that our CS approach enables optimal reconstruction from a very limited number of measurements while being robust to high noise levels. |
| Starting Page | 684 |
| Ending Page | 687 |
| File Size | 1719806 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424441259 |
| ISSN | 19457928 |
| DOI | 10.1109/ISBI.2010.5490084 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-04-14 |
| Publisher Place | Netherlands |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Compressed sensing Holography Microscopy Image reconstruction Holographic optical components Optical imaging Minimization methods Performance evaluation Optical sensors Optical diffraction signal reconstruction Compressed Sensing digital holography biological microscopy |
| Content Type | Text |
| Resource Type | Article |
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