arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2101.05080astro-ph.IMastro-ph.EP
收藏

系外行星成像数据挑战:系外行星探测的各种图像处理方法的基准

Exoplanet Imaging Data Challenge: benchmarking the various image processing methods for exoplanet detection

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. Hennin… 展开作者

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. Mueller, E. Nasedkin, B. Pairet, S. Pierard, J. -B. Ruffio, M. Samland, J. Stone, M. Van Droogenbroeck

摘要:

系外行星成像数据挑战赛是一项全社会范围的努力,旨在提供一个平台,对为系外行星直接探测设计的图像处理方法进行公平和共同的比较。为此,它在一个专门的存储库(Zenodo)上收集来自世界各地的几个高对比度地面仪器的数据,我们在这些仪器中注入了合成行星信号。数据挑战赛在CodaLab竞赛平台上举办,参赛者可以上传他们的结果。数据挑战的规格在我们的网站上发布。第一阶段于2019年9月1日启动,并于2020年10月1日结束,包括在高对比度成像领域的两种常见数据集中检测点源:在光瞳跟踪模式下以一个波长采集的数据(子挑战1,也称为ADI)和在光瞳跟踪模式下采集的多光谱数据(子挑战2,也称为ADI mSDI)。在本文中,我们描述的方法,组织的经验教训和当前的数据挑战的局限性,以及参与者提交的初步结果,这第一阶段。今后,我们计划提供对数据集和度量标准库的永久访问,以指导验证和支持专门用于行星系统高对比度成像的创新图像处理算法的出版。

英文摘要:

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. 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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑