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Algorithms for Enhancing Satellite Imagery to Discover Archaeological Finds Covered by Shadow

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Computational Science and Its Applications – ICCSA 2020 (ICCSA 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12253))

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Abstract

Very high-resolution (VHR) images proved to be an invaluable source of information even in the archaeological domain, but sometimes shadows hinder their full exploitation. To overcome such limitation, this research proposes a workflow able to analyze shadowed zones, by processing Pléiades and World-View 2 images. The case study is the archaeological site of Maltai, in the Iraqi Kurdistan Region, which presents shadowed areas to be detected. Applying de-shadowing workflow has been tested over multispectral and panchromatic images, with different invariant color spaces. The proposed methods exploit the techniques of automatic thresholding and spectral ratio in the detection of shadow regions. This approach shows a clustering of shadow pixels for an enhanced images visualization and proves its suitability for archaeological settings.

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Acknowledgements

The authors thank Prof. Daniele Morandi Bonaccorsi of University of Udine and the archaeologists Arch. Roberto Orazi and Dott. Francesca Colosi of ISPC-CNR for the opportunity to give us the input data on which to perform the research tests.

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Authors and Affiliations

  1. Dipartimento d’Ingegneria Civile, Edile e Architettura (DICEA), Università Politecnica delle Marche, Via Brecce Bianche 12, 60131, Ancona, Italy

    Stefano Chiappini, Francesco Di Stefano, Eva Savina Malinverni & Roberto Pierdicca

Authors
  1. Stefano Chiappini
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  2. Francesco Di Stefano
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  3. Eva Savina Malinverni
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  4. Roberto Pierdicca
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Corresponding author

Correspondence to Stefano Chiappini .

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Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Chair- Center of ICT/ICE, Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Cagliari, Cagliari, Italy

    Ivan Blečić

  6. Clayton School of Information Technology, Monash University, Clayton, VIC, Australia

    David Taniar

  7. Department of Information Science, Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  9. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

  10. Polytechnic University of Bari, Bari, Italy

    Carmelo Maria Torre

  11. Department of Neurology, University of Massachusetts Medical School, Worcester, MA, USA

    Yeliz Karaca

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Chiappini, S., Di Stefano, F., Malinverni, E.S., Pierdicca, R. (2020). Algorithms for Enhancing Satellite Imagery to Discover Archaeological Finds Covered by Shadow. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12253. Springer, Cham. https://doi.org/10.1007/978-3-030-58814-4_53

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  • DOI: https://doi.org/10.1007/978-3-030-58814-4_53

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-58813-7

  • Online ISBN: 978-3-030-58814-4

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