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Exoplanet imaging data challenge: benchmarking the various image processing methods for exoplanet detection

Cantalloube, F. and Gomez-Gonzalez, C. and Absil, O. and Cantero, C. and Bacher, R. and Bonse, J. M. and Bottom, M. and Dahlqvist, C.-H. and Desgrange, C. and Flasseur, O. and Fuhrmann, T. and Henning, Th. and Jensen-Clem, R. and Kenworthy, M. and Mawet, D. and Mesa, D. and Meshkat, T. and Mouillet, D. and Müller, A. and Nasedkin, E. and Pairet, B. and Piérard, S. and Ruffio, J.-B. and Samland, M. and Stone, J. and Van Droogenbroeck, M. (2020) Exoplanet imaging data challenge: benchmarking the various image processing methods for exoplanet detection. In: Adaptive Optics Systems VII. Proceedings of SPIE. No.11448. Society of Photo-Optical Instrumentation Engineers (SPIE) , Bellingham, WA, Art. No. 114485A. ISBN 9781510636835. https://resolver.caltech.edu/CaltechAUTHORS:20210108-143245499

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Abstract

The Exoplanet Imaging Data Challenge is a community-wide effort meant to offer a platform for a fair and common comparison of image processing methods designed for exoplanet direct detection. For this purpose, it gathers on a dedicated repository (Zenodo), data from several high-contrast ground-based instruments worldwide in which we injected synthetic planetary signals. The data challenge is hosted on the CodaLab competition platform, where participants can upload their results. The specifications of the data challenge are published on our website https://exoplanet-imaging-challenge.github.io/. The first phase, launched on the 1st of September 2019 and closed on the 1st of October 2020, consisted in detecting point sources in two types of common data-set in the field of high-contrast imaging: data taken in pupil-tracking mode at one wavelength (subchallenge 1, also referred to as ADI) and multispectral data taken in pupil-tracking mode (subchallenge 2, also referred to as ADI+mSDI). In this paper, we describe the approach, organisational lessons-learnt and current limitations of the data challenge, as well as preliminary results of the participants’ submissions for this first phase. In the future, we plan to provide permanent access to the standard library of data sets and metrics, in order to guide the validation and support the publications of innovative image processing algorithms dedicated to high-contrast imaging of planetary systems.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1117/12.2574803DOIArticle
http://pono.ucsd.edu/~adam/browndwarfs/spexprismRelated ItemSpeX Prism Spectral Libraries
https://exoplanet-imaging-challenge.github.ioRelated ItemExoplanet Imaging Data Challenge
https://arxiv.org/abs/2101.05080arXivDiscussion Paper
ORCID:
AuthorORCID
Cantalloube, F.0000-0002-3968-3780
Absil, O.0000-0002-4006-6237
Bottom, M.0000-0003-1341-5531
Dahlqvist, C.-H.0000-0003-4994-9244
Fuhrmann, T.0000-0002-6824-0479
Henning, Th.0000-0002-1493-300X
Jensen-Clem, R.0000-0003-0054-2953
Kenworthy, M.0000-0002-7064-8270
Mawet, D.0000-0002-8895-4735
Mesa, D.0000-0001-8467-1933
Meshkat, T.0000-0001-6126-2467
Nasedkin, E.0000-0002-9792-3121
Pairet, B.0000-0002-8731-033X
Piérard, S.0000-0001-8076-1157
Ruffio, J.-B.0000-0003-2233-4821
Samland, M.0000-0001-9992-4067
Stone, J.0000-0003-0454-3718
Van Droogenbroeck, M.0000-0001-6260-6487
Additional Information:© 2020 Society of Photo-Optical Instrumentation Engineers (SPIE). The EIDC collaboration would like to thank the GPIES collaboration and the SHINE collaboration, for providing us the pre-reduced data from Gemini/GPI and VLT/SPHERE respectively. This research has benefited from the SpeX Prism Spectral Libraries, maintained by Adam Burgasser at http://pono.ucsd.edu/~adam/browndwarfs/spexprism. This work was supported by the Fonds de la Recherche Scientifique-FNRS under Grant n F.4504.18 and by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement n 819155). T.H. acknowledges support from the European Research Council under the Horizon 2020 Framework Program via the ERC Advanced Grant Origins 832428.
Group:Astronomy Department
Funders:
Funding AgencyGrant Number
Fonds de la Recherche Scientifique (FNRS)F.4504.18
European Research Council (ERC)819155
European Research Council (ERC)832428
Subject Keywords:Exoplanet detection; High-contrast imaging; Adaptive Optics; Coronagraphy; Post-processing techniques; Data challenge
Series Name:Proceedings of SPIE
Issue or Number:11448
Record Number:CaltechAUTHORS:20210108-143245499
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210108-143245499
Official Citation:F. Cantalloube, C. Gomez-Gonzalez, O. Absil, C. Cantero, R. Bacher, M. J. Bonse, M. Bottom, C.-H. Dahlqvist, C. Desgrange, O. Flasseur, T. Fuhrmann, Th. Henning, R. Jensen-Clem, M. Kenworthy, D. Mawet, D. Mesa, T. Meshkat, D. Mouillet, A. Müller, E. Nasedkin, B. Pairet, S. Piérard, J.-B. Ruffio, M. Samland, J. Stone, and M. Van Droogenbroeck "Exoplanet imaging data challenge: benchmarking the various image processing methods for exoplanet detection", Proc. SPIE 11448, Adaptive Optics Systems VII, 114485A (13 December 2020); https://doi.org/10.1117/12.2574803
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:107384
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:09 Jan 2021 01:20
Last Modified:03 Feb 2021 23:51

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