Skip to main content
Book cover

Proceedings of the Future Technologies Conference

FTC 2021: Proceedings of the Future Technologies Conference (FTC) 2021, Volume 2 pp 201–209Cite as

Processing Drone Images with the Open Source Giwer Software Package

  • 508 Accesses

Part of the Lecture Notes in Networks and Systems book series (LNNS,volume 359)

Abstract

While various open source and commercial image processing software exist, they often lack high level image processing skills, like the flexibility to assemble custom algorithm workflows, where the experience of the evaluator can be built into the system. We have developed the Giwer (acronym for GeoImage Workflow Editing Resources) open source software package for handling, processing and analysing drone images. Giwer can be used to process large quantities of drone images – both traditional RGB and multispectral recordings. Organized into a database, the images can be searched and collected based on their attribute data. Processing is aided by a rich library of functions such as digital filterbank, classification, clustering, mathematical statistics, raster calculator, image algebra, and more. From the functions available in Giwer, arbitrary processing processes, i.e. workflows can be created, so the user can compile the most suitable processing processes based on his own knowledge and experience, which he can run not only for one image, but also for many images at once.

Keywords

  • Drone
  • Geographic information systems
  • Image processing

This is a preview of subscription content, access via your institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-030-89880-9_15
  • Chapter length: 9 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   219.00
Price excludes VAT (USA)
  • ISBN: 978-3-030-89880-9
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   279.99
Price excludes VAT (USA)
Learn about institutional subscriptions
Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.
Fig. 8.

References

  1. Image Analysis with ENVI. http://gmtgis.com/products/image-analysis-envi/

  2. ArcGIS documentation. https://desktop.arcgis.com/en/arcmap/

  3. System for Automated Geoscientific Analyses. http://www.saga-gis.org/

  4. QGIS documentation. https://docs.qgis.org/3.16/en/docs/

  5. Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: Speeded-Up robust features (SURF). Comput. Vis. Image Underst. 110, 346–359 (2008)

    CrossRef  Google Scholar 

  6. Böhner, J., McCloy, K.R., Strobl, J. (eds.): SAGA Analysis and Modelling Applications. Göttinger Geographische Abhandlungen, vol. 115, p. 130 (2006)

    Google Scholar 

  7. Jhan, J.-P., Rau, J.-Y., Haala, N.: Robust and adaptive band-to-band image transform of UAS miniature multi-lens multispectral camera. ISPRS J. Photogrammetry Remote Sens. 137, 47–60 (2018)

    CrossRef  Google Scholar 

  8. Fisher, R., Hobgen, S., Mandaya, I., Kaho, N.R., Zulkarnain, U.: Satellite image analysis and terrain modelling - A practical manual for natural resource management, disaster risk and development planning using free geospatial data and software (2017)

    Google Scholar 

  9. Jhan, J.P., Rau, J.Y.: A normalized surf for multispectral image matching and band co-registration. In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. XLII-2/W13, ISPRS Geospatial Week 2019, 10–14 June 2019. Enschede, The Netherlands (2019)

    Google Scholar 

  10. Lowe, D.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60, 91–110 (2004)

    CrossRef  Google Scholar 

  11. Kaye, S.: Can computerized terrain analysis find Boudica’s last battlefield? Br. Archaeol. 114, 30–33 (2010)

    Google Scholar 

  12. Kopecky, M., Macek, M., Wild, J.: Topographic wetness index calculation guidelines based on measured soil moisture and plant species composition. Sci. Total Environ. 757, 143785 (2021)

    CrossRef  Google Scholar 

  13. Ye, Y., Shan, J.: A local descriptor based registration method for multispectral remote sensing images with non-linear intensity differences. ISPRS J. Photogrammetry Remote Sens. 90, 83–95 (2014)

    CrossRef  Google Scholar 

Download references

Acknowledgment

Project no. ED_18-1-2019-0030 (Application-specific highly reliable IT solutions) has been implemented with the support provided from the National Research, Development and Innovation Fund of Hungary, financed under the Thematic Excellence Program funding scheme.

Author information

Authors and Affiliations

  1. ELTE Eotvos Lorand University, Budapest, Hungary

    Istvan Elek & Mate Cserep

Authors
  1. Istvan Elek
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mate Cserep
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Istvan Elek .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Prof. Dr. Kohei Arai

Rights and permissions

Reprints and Permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Elek, I., Cserep, M. (2022). Processing Drone Images with the Open Source Giwer Software Package. In: Arai, K. (eds) Proceedings of the Future Technologies Conference (FTC) 2021, Volume 2. FTC 2021. Lecture Notes in Networks and Systems, vol 359. Springer, Cham. https://doi.org/10.1007/978-3-030-89880-9_15

Download citation