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Towards Robust Evaluation of Super-Resolution Satellite Image Reconstruction

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Intelligent Information and Database Systems (ACIIDS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10751))

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Abstract

Super-resolution reconstruction (SRR) consists in processing an image or a bunch of images to generate a new image of higher spatial resolution. This problem has been intensively studied, but seldom is SRR applied in practice for satellite data. In this paper, we briefly review the state of the art on SRR algorithms and we argue that commonly adopted strategies for their evaluation do not reflect the operational conditions. We report our study on assessing the SRR outcome, relying on new quantitative measures. The obtained results allow us to outline the most important research pathways to improve the performance of SRR.

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Notes

  1. 1.

    It is understood as the distance between the centers of two neighboring pixels, however this simplification may be incorrect in the presence of some distortions.

  2. 2.

    Available at https://users.soe.ucsc.edu/~milanfar/software/sr-datasets.html (26th Oct 2017).

  3. 3.

    Available at https://www5.cs.fau.de/research/data/multi-sensor-super-resolution-datasets (26th Oct 2017).

  4. 4.

    Available at http://www.wisdom.weizmann.ac.il/~vision/SingleImageSR.html (26th Oct 2017).

  5. 5.

    Available at http://www.vision.ee.ethz.ch/ntire17 (26th Oct 2017).

  6. 6.

    Available at https://www.usgs.gov (26th Oct 2017).

  7. 7.

    Available at http://glcf.umd.edu (26th Oct 2017).

  8. 8.

    Available at https://scihub.copernicus.eu (26th Oct 2017).

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Acknowledgments

The reported work is a part of the SISPARE project run by Future Processing and funded by European Space Agency. The authors were partially supported by Institute of Informatics funds no. BK-230/RAu2/2017 (MK) and BKM-509/RAu2/2017 (JN, DK).

Author information

Authors and Affiliations

  1. Future Processing, Gliwice, Poland

    Michał Kawulok, Paweł Benecki, Jakub Nalepa, Daniel Kostrzewa & Łukasz Skonieczny

  2. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Michał Kawulok, Paweł Benecki, Jakub Nalepa & Daniel Kostrzewa

Authors
  1. Michał Kawulok
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  2. Paweł Benecki
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  5. Łukasz Skonieczny
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Corresponding author

Correspondence to Michał Kawulok .

Editor information

Editors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. Quang Binh University, Dong Hoi City, Vietnam

    Duong Hung Hoang

  3. National University of Kaohsiung, Kaohsiung, Taiwan

    Tzung-Pei Hong

  4. Rutgers University, Piscataway, New Jersey, USA

    Hoang Pham

  5. Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Kawulok, M., Benecki, P., Nalepa, J., Kostrzewa, D., Skonieczny, Ł. (2018). Towards Robust Evaluation of Super-Resolution Satellite Image Reconstruction. In: Nguyen, N., Hoang, D., Hong, TP., Pham, H., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2018. Lecture Notes in Computer Science(), vol 10751. Springer, Cham. https://doi.org/10.1007/978-3-319-75417-8_45

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  • DOI: https://doi.org/10.1007/978-3-319-75417-8_45

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