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Astronomical data fusion: recent progress and future prospects — a survey

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Abstract

Over the past year, the discovery of the first electromagnetic counterparts to sources of gravitational waves and high-energy neutrinos has brought us to the new era of ”multi-messenger” astrophysics (MMA). These new events provide deep insights into astrophysics, meanwhile, lead to the development of astronomical data fusion techniques. Each messenger carries information from different observation process and fusing all messengers can therefore provide the best understanding of the celestial objects’ attributes and expose various astrophysical phenomena. Over the decades, for the full exploitation of multi-band astronomical data, advanced unified platforms and data fusion techniques have been developed and become a research topic of interest for the astronomical community. In this paper, we present a systematic review of the popular and state-of-the-art fusion methods and platforms in different formats of astronomical data, aiming to give a comprehensive introduction to the current progress in this field; at the same time, we put forward insightful prospects for future study of multi-messenger data fusion, hoping to provide new thoughts for researchers in MMA era.

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Notes

  1. http://vizier.u-strasbg.fr/

  2. http://simbad.u-strasbg.fr/simbad/

  3. http://www.OpenSky-Query.net/

  4. http://www.starlink.ac.uk/stilts/

  5. http://www/starlink.ac.uk/topcat/

  6. http://cdsxmatch.u-strasbg.fr/xmatch/

  7. http://www.arches-fp7.eu

  8. http://www.ivoa.net/

References

  1. Abbott, B.P., Abbott, R., Abbott, T.D., et al.: Gw170817: Observation of gravitational waves from a binary neutron star inspiral. Phys. Rev. Lett. 119, 161101 (2017)

    Article  ADS  Google Scholar 

  2. Abourayan, M, Jamali, M.M., Schmidt, V.: Image fusion of astronomical images via parallel/cloud processing. In: Aerospace and Electronics Conference, pp. 100–104 (2017)

  3. Ahmad, A., Riaz, M.M., Ghafoor, A., Zaidi, T.: An improved infrared/visible fusion for astronomical images. Adv. Astron. 2015(6), 65–72 (2015)

    Google Scholar 

  4. Araya, M., Solar, M., Antognini, J.: A brief survey on the virtual observatory. New Astron. 39, 46–54 (2015)

    Article  ADS  Google Scholar 

  5. Barbey, N., Sauvage, M., Starck, J.L., Ottensamer, R., Chanial, P.: Feasibility and performances of compressed-sensing and sparse map-making with herschel/pacs data. Astron. Astrophys. 527(4–6361), 307–316 (2010)

    Google Scholar 

  6. Becla, J., Lim, K.T., Monkewitz, S., Nietosantisteban, M., Thakar, A., U, J.H.: Organizing the extremely large lsst database for real-time astronomical processing. Office of Scientific and Technical Information Technical Reports (2007)

  7. Berriman, G.B., Curkendall, D., Good, J.C., Jacob, J.C., Katz, D.S., Kong, M., Monkewitz, S., Moore, R., Prince, T.A., Williams, R.E.: Architecture for access to a compute-intensive image mosaic service in the nvo. Virtual Observ. 4846, 91–102 (2002)

    Article  ADS  Google Scholar 

  8. Berriman, G.B., Deelman, E., Good, J.C., Jacob, J.C., Katz, D.S., Kesselman, C., Laity, A.C., Prince, T.A., Singh, G., Su, M.H.: Montage: A grid-enabled engine for delivering custom science-grade mosaics on demand. In: Optimizing Scientific Return for Astronomy through Information Technologies, procspie, vol. 5493, pp. 221–232 (2004)

  9. Bertin, E.: Swarp: Resampling and co-adding fits images together. Astrophysics Source Code Library (2010)

  10. Bertin, E., Mellier, Y., Radovich, M., Missonnier, G., Didelon, P., Morin, B.: The TERAPIX Pipeline. In: Astronomical Data Analysis Software and Systems XI, Astronomical Society of the Pacific Conference Series, vol. 281, p. 228 (2002)

  11. Bijaoui, A.: A multiscale vision model adapted to the astronomical images. Signal Process. 46(3), 345–362 (1995)

    Article  MATH  Google Scholar 

  12. Bijaoui, A., Bobichon, Y., Vandame, B.: Multiscale image fusion in astronomy. Vistas Astron. 41(3), 365–372 (1997)

    Article  ADS  Google Scholar 

  13. Bobin, J., Starck, J.L.: Compressed sensing in astronomy. IEEE J. Selected Topics Signal Process. 2(5), 718–726 (2008)

    Article  ADS  Google Scholar 

  14. Bobin, J., Starck, J.L.: Compressed sensing in astronomy and remote sensing: A data fusion perspective. In: Wavelets XIII, vol. 7446, p. 74460I (2009)

  15. Boch, T., Pineau, F., Derriere, S.: The CDS cross-match service. In: Astronomical Data Analysis Software and Systems XXI, Astronomical Society of the Pacific Conference Series, vol. 461, pp. 291–294 (2012)

  16. Budavari, T., Lee, M.A.: Cross-identification of astronomical catalogs on multiple gpus. In: Astronomical Data Analysis Software and Systems XXII, vol. 475, p. 235 (2013)

  17. Budavari, T., Lee, M.A.: Xmatch: Gpu enhanced astronomic catalog cross-matching. Astrophysics Source Code Library, p. 03021 (2013)

  18. Budavári, T., Szalay, A.S.: Probabilistic cross-identification of astronomical sources. APJ 679, 301–309 (2008)

    Article  ADS  Google Scholar 

  19. Candes, E.J., Donoho, D.L.: Curvelets, multiresolution representation, and scaling laws. In: Wavelet Applications in Signal and Image Processing VIII, vol. 4119, pp. 1–12 (2000)

  20. Candes, E.J., Donoho, D.L.: Curvelets and curvilinear integrals. J. Approx. Theory 113(1), 59–90 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  21. Collet, C., Louys, M., Provost, J.N., Obero, A.: Fusion of astronomical multiband images on a markovian quadtree. In: International Conference on Information Fusion, pp. 396–403 (2002)

  22. De Prado, R.P., Garcia-Galan, S., Exposito, J.E.M., Lopez, L.R.L., Reche, R.R.: Processing astronomical image mosaic workflows with an expert broker in cloud computing. Image Process. Commun. 19(4), 5–20 (2014)

    Article  Google Scholar 

  23. Djorgovski, S.G., Williams, R.: Virtual observatory: From concept to implementation. In: From Clark Lake to the Long Wavelength Array: Bill Erickson’s Radio Science, Astronomical Society of the Pacific Conference Series, vol. 345, p. 517 (2005)

  24. Fan, D., Budavári, T., Szalay, A.S., Cui, C., Zhao, Y.: Efficient catalog matching with dropout detection. Publ. Astron. Soc. Pacific 125(924), 218–223 (2013)

    Article  ADS  Google Scholar 

  25. Fan, D., Budav, S.T.R., Norris, P.R., Hopkins, M.A.: Matching radio catalogues with realistic geometry: Application to swire and atlas. Mon. Not. R. Astron. Soc. 451(2), 1299–1305 (2015)

    Article  ADS  Google Scholar 

  26. Flitti, F., Collet, C., Slezak, E.: Wavelet domain astronomical multiband image fusion and restoration using markov quadtree and copulas. In: Signal Processing Conference, 2005 European, pp. 1–4 (2005)

  27. Flitti, F., Collet, C., Slezak, E.: Image fusion based on pyramidal multiband multiresolution markovian analysis. Signal Image Video Process. 3(3), 275–289 (2009)

    Article  MATH  Google Scholar 

  28. Fruchter, A.S.: A new method for band-limited imaging with undersampled detectors. PASP 123, 497 (2011). 1102.0292

    Article  ADS  Google Scholar 

  29. Fruchter, A.S., Hook, R.N.: Drizzle: A method for the linear reconstruction of undersampled images. Publ. Astron. Soc. Pac. 114(792), 144–152 (1998)

    Article  ADS  Google Scholar 

  30. Gorski, K.M., Hivon, E., Banday, A.J., et al.: Healpix: A framework for high-resolution discretization and fast analysis of data distributed on the sphere. Astrophys. J. 622(2), 759–771 (2005)

    Article  ADS  Google Scholar 

  31. Gray, J., Nieto-Santisteban, M.A., Szalay, A.S., Thakar, A.R., Fekete, G., O’Mullane, W., Heber, G., Rots, A.H.: There goes the neighborhood: Relational algebra for spatial data search. Computer Science (2004)

  32. Gray, J., Nieto-Santisteban, M.A., Szalay, A.S.: The zones algorithm for finding points-near-a-point or cross-matching spatial datasets. Microsoft Research (2007)

  33. Greene, G., Budavari, T., Li, N., Nietosantisteban, M., Szalay, A., Thakar, A.: Chapter 13: Web-based tools - open skyquery: Distributed database queries and crossmatching. In: The National Virtual Observatory: Tools and Techniques for Astronomical Research, vol. 382, p. 111 (2007)

  34. Gutièrrez, J.A.: Multisource data fusion for bandlimited signals: A bayesian perspective. In: American Institute of Physics, vol. 872, pp. 391–400 (2006)

  35. Gwyn, S.D.J.: MegaPipe: The MegaCam image stacking pipeline at the canadian astronomical data centre. PASP 120, 212 (2008)

    Article  ADS  Google Scholar 

  36. Gwyn, S.D.J.: The canada-france-hawaii telescope legacy survey: Stacked images and catalogs. Astron. J. 143(2), 38 (2012)

    Article  ADS  Google Scholar 

  37. Han, B., Zhang, Y.X., Zhong, S.B., Zhao, Y.H.: Astronomical data fusion tool based on PostgreSQL. Res. Astron. Astrophys. 16, 178 (2016)

    Article  ADS  Google Scholar 

  38. Hill, P., Achim, A., Bull, D.: The undecimated dual tree complex wavelet transform and its application to bivariate image denoising using a cauchy model. In: IEEE International Conference on Image Processing, pp. 1205–1208 (2012)

  39. Icecube, T., HES, S., Telescope, L., Teams, V.: Multi-messenger observations of a flaring blazar coincident with high-energy neutrino icecube-170922a. Science 361, 6398 (2018)

    Google Scholar 

  40. Jacob, J.C., Brunner, R.J., Curkendall, D.W., Djorgovski, S.G., Good, J.C., Husman, L., Kremenek, G., Mahabal, A.: YourSky: Rapid desktop access to custom astronomical image mosaics. In: Virtual Observatories, Procspie, vol. 4846, pp. 53–64 (2002)

  41. Jacob, J.C., Collier, J.B., Craymer, L.G., Curkendall, D.W.: yourskyg: Large-scale astronomical image mosaicking on the information power grid. Scalable Comput. Pract. Exper. 1, 59–75 (2006)

    Google Scholar 

  42. Jacob, J.C., Katz, D.S., Berriman, G.B., Good, J., Laity, A.C., Deelman, E., Kesselman, C., Singh, G., Su, M.H., Prince, T.A., Williams, R.: Montage: A grid portal and software toolkit for science-grade astronomical image mosaicking. ArXiv e-prints (2010)

  43. Jalobeanu, A.: Multi-source data fusion and super-resolution from astronomical images. In: Statistical Challenges in Modern Astronomy IV, vol. 371, p. 419 (2007)

  44. Jalobeanu, A., Petremand, M., Collet, C.: Bayesian fusion of hyperspectral astronomical images. In: American Institute of Physics Conference Series, American Institute of Physics Conference Series, vol. 1305, pp. 295–302 (2011)

  45. Jia, X., Luo, Q.: Multi-assignment single joins for parallel cross-match of astronomic catalogs on heterogeneous clusters. In: Proceedings of the 28th International Conference on Scientific and Statistical Database Management, pp. 1–12 (2016)

  46. Jia, X., Luo, Q., Fan, D.: Cross-matching large astronomical catalogs on heterogeneous clusters. In: IEEE 21st International Conference on Parallel and Distributed Systems, pp. 617–624 (2015)

  47. Katz, D.S., Jacob, J.C., Berriman, G.B., Good, J., Laity, A.C., Deelman, E., Kesselman, C., Singh, G.: A comparison of two methods for building astronomical image mosaics on a grid. In: Proceedings of the International Conference on Parallel Processing Workshops, pp. 85–94 (2005)

  48. Katz, D.S., Anagnostou, N., Berriman, B.G., Deelman, E, Good, J., Jacob, J.C., Kesselman, C., Laity, A., Prince, T.A., Singh, G.: Astronomical image mosaicking on a grid: Initial experiences. Engineering The Grid - Status and Perspectives (2006)

  49. Koposov, S., Bartunov, O.: Q3C, quad tree cube – the new sky-indexing concept for huge astronomical catalogues and its realization for main astronomical queries (cone search and Xmatch) in open source database PostgreSQL. In: Astronomical Data Analysis Software and Systems XV, Astronomical Society of the Pacific Conference Series, vol. 351, p. 735 (2006)

  50. Kumar, V.S., Kurc, T., Saltz, J., Abdulla, G., Kohn, S.R., Matarazzo, C.: Architectural implications for spatial object association algorithms. In: IEEE International Symposium on Parallel and Distributed Processing, pp. 1–12 (2009)

  51. Kunszt, P.Z., Szalay, A.S., Thakar, A.R.: The Hierarchical Triangular Mesh, pp 631–637. Springer, Berlin (2001)

    Google Scholar 

  52. Laity, A.C., Anagnostou, N., Berriman, G.B., Good, J.C., Jacob, J.C., Katz, D.S., Prince, T.: Montage: An astronomical image mosaic service for the NVO. In: Astronomical Data Analysis Software and Systems XIV, Astronomical Society of the Pacific Conference Series, vol. 347, p. 34 (2005)

  53. Landais, G., Ochsenbein, F., Simon, A.: TAPVizieR: A new way to access the VizieR database. In: Astronomical Data Analysis Software and Systems XXII, Astronomical Society of the Pacific Conference Series, vol. 475, p. 227 (2013)

  54. Lewis, J.J., O’Callaghan, R.J., Nikolov, S.G., Bull, D.R., Canagarajah, N.: Pixel- and region-based image fusion with complex wavelets. Inf. Fus. 8(2), 119–130 (2007)

    Article  Google Scholar 

  55. Li, L., Tang, D., Liu, T., Liu, H., Li, W., Cui, C.: Optimizing the join operation on hive to accelerate cross-matching in astronomy. In: Parallel and Distributed Processing Symposium Workshops, pp. 1735–1745 (2014)

  56. Liu, X.Y., Dong, L., Wang, J.L.: Fourier telescop imaging via sparse sampling. Opt. Precis. Eng. 18(3), 521–527 (2010)

    Google Scholar 

  57. Ma, X., Du, Z., Sun, Y., Bai, Y., Wu, S., Tchernykh, A., Xu, Y., Wu, C., Wei, J.: E-zone: A faster neighbor point query algorithm for matching spacial objects. In: International Conference on Computational Science, pp. 473–479 (2018)

  58. Makovoz, D., Khan, I.: Mosaicking with mopex. In: Astronomical Data Analysis Software and Systems XIV, Astronomical Society of the Pacific Conference Series, vol. 347, p. 81 (2005)

  59. Makovoz, D., Roby, T., Khan, I, Booth, H.: MOPEX: A software package for astronomical image processing and visualization. In: Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, procspie, vol. 6274, p. 62740C (2006)

  60. Malik, T., Szalay, A.S., Budavari, T., Thakar, A.R.: Skyquery: A webservice approach to federate databases. arXiv:cs/0211023 (2002)

  61. Masci, F.J., Fowler, J.W.: AWAIC: A WISE astronomical image co-adder. In: Astronomical Data Analysis Software and Systems XVIII, Astronomical Society of the Pacific Conference Series, vol. 411, p. 67, 0812.4310 (2009)

  62. Masias, M., Freixenet, J., Lladó, X., Peracaula, M.: A review of source detection approaches in astronomical images. Mon. Not. R. Astron. Soc. 422 (2), 1674–1689 (2012)

    Article  ADS  Google Scholar 

  63. Mi, C., Chen, Q., Liu, T.: An efficient cross-match implementation based on directed join algorithm in mapreduce. In: Proceedings of the 2011 Fourth IEEE International Conference on Utility and Cloud Computing, IEEE Computer Society, UCC ’11, pp. 41–48 (2011)

  64. Motch, C., Carrera, F., Genova, F., et al.: The arches project. In: Astronomical Data Analysis Software and Systems XXV, Astronomical Society of the Pacific Conference Series, vol. 512, p. 165 (2017)

  65. Nietosantisteban, M.A., Thakar, A.R., Szalay, A.S.: Cross-matching very large datasets. Astronomy (2006)

  66. Nietosantisteban, M.A., Thakar, A.R., Szalay, A.S., Gray, J.: Large-scale query and xmatch, entering the parallel zone. In: Astronomical Data Analysis Software and Systems XV, Astronomical Society of the Pacific Conference Series, vol. 351, p. 493 (2007)

  67. Ochsenbein, F., Bauer, P., Marcout, J.: The vizier database of astronomical catalogues. Astron. Astrophys. Suppl. 143(1), 23–32 (2000)

    Article  ADS  Google Scholar 

  68. Peng, D.U., Ren, J.J., Pan, J.C., Luo, A.: New cross-matching algorithm in large-scale catalogs with threadpool technique. Sci. Chin: Phys. Mech. Astron. 57 (3), 577–583 (2014)

    Article  ADS  Google Scholar 

  69. Petremand, M., Jalobeanu, A., Collet, C.: Optimal bayesian fusion of large hyperspectral astronomical observations. Statist. Methodol. 9(1a2), 44–54 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  70. Pineau, F., Boch, T., Derriere, S.: Efficient and scalable cross-matching of (very) large catalogs. In: Astronomical Data Analysis Software and Systems XX, Astronomical Society of the Pacific Conference Series, vol. 442, p. 85 (2011)

  71. Pineau, F.X., Derriere, S., Motch, C., Carrera, F.J., Genova, F., Michel, L., Mingo, B., Mints, A., Nebot Gómez-Morán, A., Rosen, S.R., Ruiz Camuñas, A.: Probabilistic multi-catalogue positional cross-match. AAP 597, A89 (2017)

    Article  Google Scholar 

  72. Riccio, G., Brescia, M., Cavuoti, S., et al.: C3, a command-line catalog cross-match tool for large astrophysical catalogs. Publ. Astron. So. Pac. 129(972), 024005 (2017)

    Article  ADS  Google Scholar 

  73. Salvato, M., Buchner, J., Budavari, T., Dwelly, T., Merloni, A., Brusa, M., Rau, A., Fotopoulou, S., Nandra, K.: Finding counterparts for all-sky x-ray surveys with nway: A bayesian algorithm for cross-matching multiple catalogues. Mon. Not. R. Astron. Soc. 473, 4937–4955 (2017)

    Article  ADS  Google Scholar 

  74. Soumagnac, M.T., Ofek, E.O.: catshtm: A tool for fast accessing and cross-matching large astronomical catalogs. PASP 130(7), 075002 (2018)

    Article  ADS  Google Scholar 

  75. Starck, J.L.: Multiscale methods in astronomy: Beyond wavelets. Astron. Data Anal. Softw. Syst. XI(281), 391 (2002)

    ADS  Google Scholar 

  76. Starck, J.L., Donoho, D.L., CandÚs, E.J.: Astronomical image representation by the curvelet transform. Astron. Astrophys. 398(2), 785–800 (2002)

    Article  ADS  Google Scholar 

  77. Takeda, H., Farsiu, S., Christou, J., Milanfar, P.: Super-drizzle: Applications of adaptive kernel regression in astronomical imaging. in: The Advanced Maui Optical and Space Surveillance Technologies Conference, p. E27 (2006)

  78. Takeda, H., Farsiu, S., Milanfar, P.: Kernel regression for image processing and reconstruction. IEEE Trans. Image Process. 16(2), 349–366 (2007)

    Article  ADS  MathSciNet  Google Scholar 

  79. Taylor, M.: Topcat – tool for operations on catalogues and tables. Starlink User Note, p. 253 (2011)

  80. Taylor, M.B.: STILTS - a package for command-line processing of tabular data. In: Astronomical Data Analysis Software and Systems XV, Astronomical Society of the Pacific Conference Series, vol. 351, p. 666 (2006)

  81. Wang, L., Li, G.L.: How to co-add images? I. A new iterative method for image reconstruction of dithered observations. Res. Astron. Astrophys. 17, 100 (2017)

    Article  ADS  Google Scholar 

  82. Wang, S., Zhao, Y., Luo, Q., Wu, C., Yang, X.: Accelerating in-memory cross match of astronomical catalogs. In: IEEE International Conference on E-Science, pp. 326–333 (2013)

  83. Wenger, M., Ochsenbein, F., Egret, D., et al.: The simbad astronomical database. The cds reference database for astronomical objects. Astron. Astrophys. Suppl. 143(1), 9–22 (2000)

    Article  ADS  Google Scholar 

  84. Zhang, Z., Blum, R.: A categorization of multiscale-decomposition-based image fusion schemes with a performance study for a digital camera application. Proc. IEEE 87(8), 1315–1326 (1999)

    Article  Google Scholar 

  85. Zhao, Q., Sun, J., Yu, C., et al.: A paralleled large-scale astronomical cross-matching function. In: Proceedings of the 9th International Conference on Algorithms and Architectures for Parallel Processing, pp. 604–614 (2009)

  86. Zhou, W.P., Li, Y., Liu, Q.S., Wang, G.D., Liu, Y.: Fast compression and reconstruction of astronomical images based on compressed sensing. Res. Astron. Astrophys. 9, 1207–1214 (2014)

    Article  ADS  Google Scholar 

  87. Zhu, H.J., Han, B.C., Qiu, B.: Survey of Astronomical Image Processing Methods. Springer International Publishing (2015)

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Acknowledgements

This work is supported by the Joint Research Fund in Astronomy (U1731243, U1731125, U1531111) under cooperative agreement between the National Natural Science Foundation of China (NSFC) and Chinese Academy of Sciences (CAS), the National Natural Science Foundation of China (11573019, 61602336).

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  1. College of Intelligence and Computing, Tianjin University, Tianjin, 300350, China

    Ce Yu, Bingyao Li, Jian Xiao, Chao Sun, Shanjiang Tang & Chongke Bi

  2. National Astronomical Observatories, Chinese Academy of Sciences, Beijing, 100101, China

    Chenzhou Cui & Dongwei Fan

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  1. Ce Yu
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Yu, C., Li, B., Xiao, J. et al. Astronomical data fusion: recent progress and future prospects — a survey. Exp Astron 47, 359–380 (2019). https://doi.org/10.1007/s10686-019-09633-z

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