Towards Landmine Detection Using Ubiquitous Satellite Imaging. Elkazaz, S., Hussein, M. E., El-Mahdy, A., & Ishikawa, H. In Bebis, G., Boyle, R., Parvin, B., Koracin, D., Porikli, F., Skaff, S., Entezari, A., Min, J., Iwai, D., Sadagic, A., Scheidegger, C., & Isenberg, T., editors, Advances in Visual Computing, of Lecture Notes in Computer Science, pages 257–267, 2016. Springer International Publishing. abstract bibtex Despite the tremendous number of landmines worldwide, existing methods for landmine detection still suffer from high scanning costs and times. Utilizing ubiquitous thermal infrared satellite imaging might potentially be an alternative low-cost method, relying on processing big image data collected over decades. In this paper we study this alternative, focusing on assessing the utility of resolution enhancement using state-of-the art super-resolution algorithms in landmine detection. The major challenge is the relatively limited number of thermal satellite images available for a given location, which makes the possible magnification factor extremely low for landmine detection. To facilitate the study, we generate equivalent satellite images for various landmine distributions. We then estimate the detection accuracy from a naive landmine detector on the super-resolution images. While our proposed methodology might not be useful for anti-personal landmines, the experimental results show a promising detection rates for large anti-tank landmines.
@inproceedings{elkazaz_towards_2016,
title = {Towards Landmine Detection Using Ubiquitous Satellite Imaging},
rights = {All rights reserved},
isbn = {978-3-319-50835-1},
series = {Lecture Notes in Computer Science},
abstract = {Despite the tremendous number of landmines worldwide, existing methods for landmine detection still suffer from high scanning costs and times. Utilizing ubiquitous thermal infrared satellite imaging might potentially be an alternative low-cost method, relying on processing big image data collected over decades. In this paper we study this alternative, focusing on assessing the utility of resolution enhancement using state-of-the art super-resolution algorithms in landmine detection. The major challenge is the relatively limited number of thermal satellite images available for a given location, which makes the possible magnification factor extremely low for landmine detection. To facilitate the study, we generate equivalent satellite images for various landmine distributions. We then estimate the detection accuracy from a naive landmine detector on the super-resolution images. While our proposed methodology might not be useful for anti-personal landmines, the experimental results show a promising detection rates for large anti-tank landmines.},
pages = {257--267},
booktitle = {Advances in Visual Computing},
publisher = {Springer International Publishing},
author = {Elkazaz, Sahar and Hussein, Mohamed E. and El-Mahdy, Ahmed and Ishikawa, Hiroshi},
editor = {Bebis, George and Boyle, Richard and Parvin, Bahram and Koracin, Darko and Porikli, Fatih and Skaff, Sandra and Entezari, Alireza and Min, Jianyuan and Iwai, Daisuke and Sadagic, Amela and Scheidegger, Carlos and Isenberg, Tobias},
year = {2016},
langid = {english},
keywords = {Ground Penetration Radar, Image Prior Model, Random Guesser, Satellite Image, Thermal Satellite Image}
}
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The major challenge is the relatively limited number of thermal satellite images available for a given location, which makes the possible magnification factor extremely low for landmine detection. To facilitate the study, we generate equivalent satellite images for various landmine distributions. We then estimate the detection accuracy from a naive landmine detector on the super-resolution images. 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Utilizing ubiquitous thermal infrared satellite imaging might potentially be an alternative low-cost method, relying on processing big image data collected over decades. In this paper we study this alternative, focusing on assessing the utility of resolution enhancement using state-of-the art super-resolution algorithms in landmine detection. The major challenge is the relatively limited number of thermal satellite images available for a given location, which makes the possible magnification factor extremely low for landmine detection. To facilitate the study, we generate equivalent satellite images for various landmine distributions. We then estimate the detection accuracy from a naive landmine detector on the super-resolution images. 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