Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12386/29492
Title: | Approximate nonnegative matrix factorization algorithm for the analysis of angular differential imaging data | Authors: | ARCIDIACONO, CARMELO Simoncini, V. |
Issue Date: | 2018 | Volume: | Adaptive Optics Systems VI | Editors: | Close, Laird M.; Schreiber, Laura; Schmidt, Dirk | Series: | PROCEEDINGS OF SPIE | Number: | 10703 | First Page: | 1070331 | Abstract: | The angular differential imaging (ADI) is used to improve contrast in high resolution astronomical imaging. An example is the direct imaging of exoplanet in camera fed by Extreme Adaptive Optics. The subtraction of the main dazzling object to observe the faint companion was improved using Principal Component Analysis (PCA). It factorizes the positive astronomical frames into positive and negative components. On the contrary, the Nonnegative Matrix Factorization (NMF) uses only positive components, mimicking the actual composition of the long exposure images. | Conference Name: | Adaptive Optics Systems VI | Conference Place: | Austin, Texas, United States | Conference Date: | 10 - 15 June, 2018 | URI: | http://hdl.handle.net/20.500.12386/29492 | URL: | https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10703/2311681/Approximate-nonnegative-matrix-factorization-algorithm-for-the-analysis-of-angular/10.1117/12.2311681.full https://arxiv.org/abs/1807.01208 |
ISSN: | 0277-786X | ISBN: | 9781510619593 9781510619609 |
DOI: | 10.1117/12.2311681 | Bibcode ADS: | 2018SPIE10703E..31A | Fulltext: | open |
Appears in Collections: | 3.01 Contributi in Atti di convegno |
Files in This Item:
File | Description | Size | Format | |
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1070331.pdf | Pdf editoriale | 1.01 MB | Adobe PDF | View/Open |
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