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VIP: Vortex Image Processing package for high-contrast direct imaging

Gomez Gonzalez, Carlos Alberto and Wertz, Olivier and Absil, Olivier and Christiaens, Valentin and Defrère, Denis and Mawet, Dimitri and Milli, Julien and Absil, Pierre-Antoine and Van Droogenbroeck, Marc and Cantalloube, Faustine and Hinz, Philip M. and Skemer, Andrew J. and Karlsson, Mikael and Surdej, Jean (2017) VIP: Vortex Image Processing package for high-contrast direct imaging. Astronomical Journal, 154 (1). Art. No. 7. ISSN 1538-3881. doi:10.3847/1538-3881/aa73d7.

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We present the Vortex Image Processing (VIP) library, a python package dedicated to astronomical high-contrast imaging. Our package relies on the extensive python stack of scientific libraries and aims to provide a flexible framework for high-contrast data and image processing. In this paper, we describe the capabilities of VIP related to processing image sequences acquired using the angular differential imaging (ADI) observing technique. VIP implements functionalities for building high-contrast data processing pipelines, encompassing pre- and post-processing algorithms, potential source position and flux estimation, and sensitivity curve generation. Among the reference point-spread function subtraction techniques for ADI post-processing, VIP includes several flavors of principal component analysis (PCA) based algorithms, such as annular PCA and incremental PCA algorithms capable of processing big datacubes (of several gigabytes) on a computer with limited memory. Also, we present a novel ADI algorithm based on non-negative matrix factorization, which comes from the same family of low-rank matrix approximations as PCA and provides fairly similar results. We showcase the ADI capabilities of the VIP library using a deep sequence on HR 8799 taken with the LBTI/LMIRCam and its recently commissioned L-band vortex coronagraph. Using VIP, we investigated the presence of additional companions around HR 8799 and did not find any significant additional point source beyond the four known planets. VIP is available at and is accompanied with Jupyter notebook tutorials illustrating the main functionalities of the library.

Item Type:Article
Related URLs:
URLURL TypeDescription Paper
Gomez Gonzalez, Carlos Alberto0000-0003-2050-1710
Wertz, Olivier0000-0003-3849-2285
Absil, Olivier0000-0002-4006-6237
Christiaens, Valentin0000-0002-0101-8814
Defrère, Denis0000-0003-3499-2506
Mawet, Dimitri0000-0002-8895-4735
Milli, Julien0000-0001-9325-2511
Absil, Pierre-Antoine0000-0003-2946-4178
Hinz, Philip M.0000-0002-1954-4564
Skemer, Andrew J.0000-0001-6098-3924
Karlsson, Mikael0000-0002-2011-0851
Surdej, Jean0000-0002-7005-1976
Additional Information:© 2017 The American Astronomical Society. Received 2016 June 23; revised 2017 May 9; accepted 2017 May 15; published 2017 June 13. The authors would like to thank the whole python open-source community and the developers of the powerful open-source stack of scientific libraries. Special thanks to the creators of the Ipython Jupyter application. We also thank Elsa Huby, Maddalena Reggiani, and Rebecca Jensen-Clem for useful discussions and early bug reports. Finally, we thank the referee, Tim Brandt, for his constructive questions and valuable comments. The research leading to these results has received funding from the European Research Council Under the European Union's Seventh Framework Program (ERC Grant Agreement n. 337569) and from the French Community of Belgium through an ARC grant for Concerted Research Action. V.C. acknowledges financial support provided by Millennium Nucleus grant RC130007 (Chilean Ministry of Economy). The LBTI is funded by the National Aeronautics and Space Administration as part of its Exoplanet Exploration Program. The LBT is an international collaboration among institutions in the United States, Italy, and Germany. LBT Corporation partners are The University of Arizona on behalf of the Arizona university system; Instituto Nazionale di Astrofisica, Italy; LBT Beteiligungsgesellschaft, Germany, representing the Max-Planck Society, the Astrophysical Institute Potsdam, and Heidelberg University; The Ohio State University, and The Research Corporation, on behalf of The University of Notre Dame, University of Minnesota and University of Virginia. This research was supported by NASA's Origins of Solar Systems Program, grant NNX13AJ17G. Software: numpy (van der Walt et al. 2011), scipy (Jones et al. 2001), matplotlib (Hunter 2007), astropy (Astropy Collaboration et al. 2013), photutils (Bradley et al. 2016), scikit-learn (Pedregosa et al. 2011), pandas (McKinney 2010), scikit-image (van der Walt et al. 2014), emcee (Foreman-Mackey et al. 2013), OpenCV (Bradski 2000), SAOImage DS9, nestle.
Group:Astronomy Department
Funding AgencyGrant Number
European Research Council (ERC)337569
Communauté française de Belgique – Actions de recherche concertéesUNSPECIFIED
Millennium NucleusRC130007
Subject Keywords:methods: data analysis; planetary systems; planets and satellites: detection; techniques: high angular resolution; techniques: image processing
Issue or Number:1
Record Number:CaltechAUTHORS:20170518-102114519
Persistent URL:
Official Citation:Carlos Alberto Gomez Gonzalez et al 2017 AJ 154 7
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:77565
Deposited By: Joy Painter
Deposited On:18 May 2017 17:33
Last Modified:15 Nov 2021 17:32

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