Skip to main content
Log in

Image and Data Processing for InSight Lander Operations and Science

  • Published:
Space Science Reviews Aims and scope Submit manuscript

Abstract

The Instrument Site Selection and deployment for the upcoming Mars InSight (Interior Exploration using Seismic Investigations, Geodesy and Heat Transport) Lander is highly dependent on image products, particularly mosaics, created from the Instrument Deployment Camera (IDC) and Instrument Context Camera (ICC). When data are downlinked, the Multimission Image Processing Lab (MIPL) at JPL will process image and instrument data to aid in the deployment and monitoring of these instruments. MIPL’s functions include raw telemetry processing, stereo correlation, mosaic generation, terrain mesh generation, radiometric correction, pointing correction (bundle adjustment), and the creation of products such as instrument deployment maps, surface normal products, slope products, XYZ point clouds, and roughness map layers. A software pipeline performs systematic, automated execution of the programs that create these products on every image and stereo pair received, while the pointing correction and most mosaics are hand-generated by the MIPL team members for testing and surface operations. Several mission operations software packages are used to view, query, and analyze the processed images and mosaics for placing the main science instruments for the mission.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23
Fig. 24
Fig. 25
Fig. 26
Fig. 27
Fig. 28
Fig. 29
Fig. 30
Fig. 31
Fig. 32
Fig. 33
Fig. 34
Fig. 35
Fig. 36
Fig. 37
Fig. 38
Fig. 39

Similar content being viewed by others

References

  • C. Acton, S. Slavney, R.E. Arvidson, L.R. Gaddis, M. Gordon, S. Lavoie, The planetary data system. Lunar Planet. Inf. Bull. 150, 2–11 (2017)

    Google Scholar 

  • S. Agarawal, K. Mierle, et al. (web) (2018). http://ceres-solver.org

  • D. Alexander, R. Deen, Mars Science Laboratory Project Software Interface Specification (SIS); Camera & LIBS Experiment Data Record (EDR) and Reduced Data Record (RDR) Data Products, version 4.0. JPL Doc. D-38107, data set MSL-M-NAVCAM-2-EDR-V1.0, NASA Planetary Data System (2017)

  • D.A. Alexander et al., Processing of Mars Exploration Rover imagery for science and operations planning. J. Geophys. Res. 111, E02S02 (2006). https://doi.org/10.1029/2005JE002462

    Article  Google Scholar 

  • W.B. Banerdt et al., The InSight mission for 2018, in 48th Lunar and Planet. Sci. Conf., Abstract 1896 (2017)

    Google Scholar 

  • F.J. Calef, H.E. Gengl, T. Soliman, S.P. Abercrombie, M.W. Powell, MMGIS: a multi-mission geographic information system for in situ Mars operations, in 48th Lunar and Planetary Science Conference (2017), #2541

    Google Scholar 

  • CCSDS, Standard Formatted Data Units—Structure and Construction Rules. Recommendation for Space Data System Standards (No 2). CCSDS 620.0-B-2. Blue Book (1992). https://public.ccsds.org/Pubs/622x0b1.pdf

  • C. Cheng, R. Patel, E. Sayfi, H. Lee, Multi-mission automated instrument product generation implemented capabilities, in IEEE Aerospace Conference, Big Sky, Montana, March 2008 (2008a)

    Google Scholar 

  • C. Cheng et al., Using a multi-mission automated system for product generation, in SpaceOps 2008, Heidelberg, Germany, May (2008b)

    Google Scholar 

  • CIE, Commission internationale de l’eclairage proceedings, 1931 (Cambridge University Press, Cambridge, 1932)

    Google Scholar 

  • P. Cignoni, M. Callieri, M. Corsini, M. Dellepiane, F. Ganovelli, G. Ranzuglia, MeshLab: an open-source mesh processing tool, in Sixth Eurographics Italian Chapter Conference (2008), pp. 129–136

    Google Scholar 

  • R.G. Deen, Cost savings through multimission code reuse for Mars image products, in 5th Int’l Symposium on Reducing the Cost of Spacecraft Ground Systems and Operations (RCSGSO), Deep Space Comm. and Nav. Syst. Cent. of Excellence (DESCANSO), Pasadena, California, 2003 (2003)

    Google Scholar 

  • R.G. Deen, J.J. Lorre, Seeing in three dimensions: correlation and triangulation of Mars Exploration Rover imagery, in International Conference on Systems, Man, and Cybernetics, Inst. of Electr. and Electron. Eng., Waikoloa, Hawaii, 2005 (2005)

    Google Scholar 

  • R. Deen, A. Chen, K. Capraro, H. Gengl, S. Algermissen, N. Ruoff, O. Pariser, Pointing correction for Mars surface mosaics, in 2nd Planetary Data Workshop, Abstract #7055, Flagstaff, AZ (2015a)

    Google Scholar 

  • R.G. Deen, S.C. Mayer, E.M. Sayfe, C. Radulescu, S.R. Levoe, VICAR open source release, in 2nd Planetary Data Workshop, Abstract #7059, Flagstaff, AZ (2015b)

    Google Scholar 

  • R. Deen, P. Zamani, H. Abarca, J. Maki, InSight software interface specification: Camera Experiment Data Record (EDR) and Reduced Data Record (RDR) data products, in NASA Planetary Data System (2018, in press)

    Google Scholar 

  • W.M. Folkner et al., The rotation and interior structure experiment on the InSight mission to Mars. Space Sci. Rev. 214(5), 100 (2018)

    Article  ADS  Google Scholar 

  • B.A. Galler, M.J. Fisher, An improved equivalence algorithm. Commun. ACM 7(5), 301–303 (1964) (cf. p. 56)

    Article  Google Scholar 

  • D.B. Gennery, Generalized camera calibration including fish-eye lenses. Int. J. Comput. Vis. 68(3), 239–266 (2006). https://doi.org/10.1007/s11263-006-5168-1

    Article  Google Scholar 

  • S.B. Goldberg, M.W. Maimone, L. Matthies, Stereo vision and rover navigation software for planetary exploration, in 2002 IEEE Aerospace Conference, Inst. of Electr. and Electron. Eng., Big Sky, Montana (2002)

    Google Scholar 

  • M. Golombek, D. Kipp, N. Warner, I.J. Daubar, R. Fergason, R. Kirk, R. Beyer, A. Huertas, S. Piqueux, N.E. Putzig, B.A. Campbell, G.A. Morgan, C. Charalambous, W.T. Pike, K. Gwinner, F. Calef, D. Kass, M. Mischna, J. Ashley, C. Bloom, N. Wigton, T. Hare, C. Schwartz, H. Gengl, L. Redmond, M. Trautman, J. Sweeney, C. Grima, I.B. Smith, E. Sklyanskiy, M. Lisano, J. Benardini, S. Smrekar, P. Lognonné, W.B. Banerdt, Selection of the InSight landing site. Space Sci. Rev. 211, 5–95 (2017). https://doi.org/10.1007/s11214-016-0321-9

    Article  ADS  Google Scholar 

  • M. Golombek et al., Geology and physical properties investigations by the InSight lander. Space Sci. Rev. 214(5), 84 (2018)

    Article  ADS  Google Scholar 

  • K. Grimes, J. Padams, G. Hollins, Web resource platform, in 3nd Planetary Data Workshop, Flagstaff, AZ (2017). Abstract #7131

    Google Scholar 

  • A.W. Gruen, E.P. Baltsavias, Geometrically constrained multiphoto matching. Photogramm. Eng. Remote Sens. 54(5), 633–641 (1988). 1988

    Google Scholar 

  • T. Huang, Component architecture—the software architecture for mission requirements, in 5th Int’l Symposium on Reducing the Cost of Spacecraft Ground Systems and Operations (RCSGSO), Deep Space Comm. and Nav. Syst. Cent. of Excellence (DESCANSO), Pasadena, California, 2003 (2003)

    Google Scholar 

  • ITU, International Telecommunication Union Radiocommunication Sector, Recommendation ITU-R BT.709-6, “Parameter values for the HDTV standards for production and international programme exchange”, June 2015, BT Series, Broadcasting Service, Television, Electronic Publication Geneva, 2015 (2015). http://www.itu.int/rec/R-REC-BT.709-6-201506-I/en

  • S.K. LaVoie et al., Processing and analysis of Mars Pathfinder science data at the Jet Propulsion Laboratory’s Science Data Processing Systems section. J. Geophys. Res. 104(E4), 8831–8852 (1999)

    Article  ADS  Google Scholar 

  • P. Lognonné et al., SEIS: insight’s seismic experiment for internal structure of Mars. Space Sci. Rev. 215, 12 (2019)

    Article  ADS  Google Scholar 

  • D.G. Lowe, Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60, 91 (2004). https://doi.org/10.1023/B:VISI.0000029664.99615.94

    Article  Google Scholar 

  • J. Maki, D. Thiessen, A. Pourangi, P. Kobzeff, T. Litwin, L. Scherr, S. Elliott, A. Dingizian, M. Maimone, The Mars Science Laboratory engineering cameras. Space Sci. Rev. 170, 77–93 (2012). https://doi.org/10.1007/s11214-012-9882-4

    Article  ADS  Google Scholar 

  • J.N. Maki, M. Golombek, R. Deen, H. Abarca, C. Sorice, T. Goodsall, M. Schwochert, M. Lemmon, A. Trebi-Ollennu, W.B. Banerdt, The color cameras on the InSight lander. Space Sci. Rev. 214(6), 105 (2018)

    Article  ADS  Google Scholar 

  • OBJ_Format (web). https://en.wikipedia.org/wiki/Wavefront_.obj_file

  • C.F. Olson, L.H. Matthies, J.R. Wright, R. Li, K. Di, Visual terrain mapping for Mars exploration. Comput. Vis. Image Underst. 105(1), 73–85 (2007)

    Article  Google Scholar 

  • Open_Inventor (web). https://www.openinventor.com

  • PDS_Imaging_Node (web). https://pds-imaging.jpl.nasa.gov/search

  • PDS_Marsviewer (web). https://pds-imaging.jpl.nasa.gov/tools/marsviewer/

  • SPICE (web). https://naif.jpl.nasa.gov/naif/index.html

  • T. Spohn et al., The heat flow and physical properties package (HP3) for the InSight mission. Space Sci. Rev. 214(5), 96 (2018)

    Article  ADS  Google Scholar 

  • J.E. Tomakyo, Computers in spaceflight: the NASA experience. Encyclopedia of Computer Science and Technology (Supplement 3), vol. 18, 292 (1988), NASA-CR-182505

    Google Scholar 

  • A. Trebi-Ollennu et al., InSight Mars lander robotics instrument deployment system. Space Sci. Rev. 214(5), 93 (2018)

    Article  ADS  Google Scholar 

  • B. Triggs, P. McLauchlan, R. Hartley, A. Fitzgibbon, Bundle adjustment—a modern synthesis, in ICCV ’99: Proceedings of the International Workshop on Vision Algorithms (Springer, Berlin, 1999), pp. 298–372

    Google Scholar 

  • VICAR (web). http://www-mipl.jpl.nasa.gov/vicar.html

  • D. Watson, An implementation of natural neighbor interpolation (1994). https://books.google.com/books?id=jMmjcQAACAAJ

  • G. Wyszecki, W.S. Stiles, Color Science: Concepts and Methods, Quantitative Data and Formulae, 2nd edn. (Wiley, New York, 1982). 1982

    Google Scholar 

  • Z. Xing, F. Sayfi, Webification (W10N)—data on the web platform, in 2nd Planetary Data Workshop, Flagstaff, AZ (2015). Abstract #7066

    Google Scholar 

  • Y. Yakimovsky, R. Cunningham, A system for extracting three dimensional measurements from a stereo pair of TV cameras. Comput. Graph. Image Process. 7, 195–210 (1978)

    Article  ADS  Google Scholar 

Download references

Acknowledgements

This work was supported by the InSight Project at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. The authors would like to thank Cecilia Cheng, Ashitey Trebi-Ollennu, Steven Myint, Omair Khan, Philip Bailey, Khaled Ali, and Won Kim for their contributions to the work described in this paper. This paper is InSight Contribution Number 75.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to H. Abarca.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The InSight Mission to Mars II

Edited by William B. Banerdt and Christopher T. Russell

Government sponsorship acknowledged

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Abarca, H., Deen, R., Hollins, G. et al. Image and Data Processing for InSight Lander Operations and Science. Space Sci Rev 215, 22 (2019). https://doi.org/10.1007/s11214-019-0587-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11214-019-0587-9

Keywords

Navigation