Generating impact maps from automatically detected bomb craters in aerial wartime images using marked point processes

Publikation: Beitrag in FachzeitschriftKonferenzaufsatz in FachzeitschriftForschungPeer-Review

Autoren

  • Christian Kruse
  • Franz Rottensteiner
  • Thorsten Hoberg
  • Marcel Ziems
  • Julia Rebke
  • Christian Heipke

Externe Organisationen

  • Landesamt für Geoinformation und Landesvermessung Niedersachsen (LGLN)
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Seiten (von - bis)127-134
Seitenumfang8
FachzeitschriftISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Jahrgang4
Ausgabenummer3
PublikationsstatusVeröffentlicht - 23 Apr. 2018
Veranstaltung2018 ISPRS TC III Mid-Term Symposium on Developments, Technologies and Applications in Remote Sensing - Beijing, China
Dauer: 7 Mai 201810 Mai 2018

Abstract

The aftermath of wartime attacks is often felt long after the war ended, as numerous unexploded bombs may still exist in the ground. Typically, such areas are documented in so-called impact maps which are based on the detection of bomb craters. This paper proposes a method for the automatic detection of bomb craters in aerial wartime images that were taken during the Second World War. The object model for the bomb craters is represented by ellipses. A probabilistic approach based on marked point processes determines the most likely configuration of objects within the scene. Adding and removing new objects to and from the current configuration, respectively, changing their positions and modifying the ellipse parameters randomly creates new object configurations. Each configuration is evaluated using an energy function. High gradient magnitudes along the border of the ellipse are favored and overlapping ellipses are penalized. Reversible Jump Markov Chain Monte Carlo sampling in combination with simulated annealing provides the global energy optimum, which describes the conformance with a predefined model. For generating the impact map a probability map is defined which is created from the automatic detections via kernel density estimation. By setting a threshold, areas around the detections are classified as contaminated or uncontaminated sites, respectively. Our results show the general potential of the method for the automatic detection of bomb craters and its automated generation of an impact map in a heterogeneous image stock.

ASJC Scopus Sachgebiete

Zitieren

Generating impact maps from automatically detected bomb craters in aerial wartime images using marked point processes. / Kruse, Christian; Rottensteiner, Franz; Hoberg, Thorsten et al.
in: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Jahrgang 4, Nr. 3, 23.04.2018, S. 127-134.

Publikation: Beitrag in FachzeitschriftKonferenzaufsatz in FachzeitschriftForschungPeer-Review

Kruse, C, Rottensteiner, F, Hoberg, T, Ziems, M, Rebke, J & Heipke, C 2018, 'Generating impact maps from automatically detected bomb craters in aerial wartime images using marked point processes', ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Jg. 4, Nr. 3, S. 127-134. https://doi.org/10.5194/isprs-annals-IV-3-127-2018, https://doi.org/10.15488/3442
Kruse, C., Rottensteiner, F., Hoberg, T., Ziems, M., Rebke, J., & Heipke, C. (2018). Generating impact maps from automatically detected bomb craters in aerial wartime images using marked point processes. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 4(3), 127-134. https://doi.org/10.5194/isprs-annals-IV-3-127-2018, https://doi.org/10.15488/3442
Kruse C, Rottensteiner F, Hoberg T, Ziems M, Rebke J, Heipke C. Generating impact maps from automatically detected bomb craters in aerial wartime images using marked point processes. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2018 Apr 23;4(3):127-134. doi: 10.5194/isprs-annals-IV-3-127-2018, 10.15488/3442
Kruse, Christian ; Rottensteiner, Franz ; Hoberg, Thorsten et al. / Generating impact maps from automatically detected bomb craters in aerial wartime images using marked point processes. in: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2018 ; Jahrgang 4, Nr. 3. S. 127-134.
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abstract = "The aftermath of wartime attacks is often felt long after the war ended, as numerous unexploded bombs may still exist in the ground. Typically, such areas are documented in so-called impact maps which are based on the detection of bomb craters. This paper proposes a method for the automatic detection of bomb craters in aerial wartime images that were taken during the Second World War. The object model for the bomb craters is represented by ellipses. A probabilistic approach based on marked point processes determines the most likely configuration of objects within the scene. Adding and removing new objects to and from the current configuration, respectively, changing their positions and modifying the ellipse parameters randomly creates new object configurations. Each configuration is evaluated using an energy function. High gradient magnitudes along the border of the ellipse are favored and overlapping ellipses are penalized. Reversible Jump Markov Chain Monte Carlo sampling in combination with simulated annealing provides the global energy optimum, which describes the conformance with a predefined model. For generating the impact map a probability map is defined which is created from the automatic detections via kernel density estimation. By setting a threshold, areas around the detections are classified as contaminated or uncontaminated sites, respectively. Our results show the general potential of the method for the automatic detection of bomb craters and its automated generation of an impact map in a heterogeneous image stock.",
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AU - Kruse, Christian

AU - Rottensteiner, Franz

AU - Hoberg, Thorsten

AU - Ziems, Marcel

AU - Rebke, Julia

AU - Heipke, Christian

N1 - Funding Information: The authors would like to thank the State Office for Geoinformation and Surveying of Lower Saxony and its explosive ordnance disposal service as a department of the regional directorate Hamelin-Hanover for providing the data and the financial support to this project.

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N2 - The aftermath of wartime attacks is often felt long after the war ended, as numerous unexploded bombs may still exist in the ground. Typically, such areas are documented in so-called impact maps which are based on the detection of bomb craters. This paper proposes a method for the automatic detection of bomb craters in aerial wartime images that were taken during the Second World War. The object model for the bomb craters is represented by ellipses. A probabilistic approach based on marked point processes determines the most likely configuration of objects within the scene. Adding and removing new objects to and from the current configuration, respectively, changing their positions and modifying the ellipse parameters randomly creates new object configurations. Each configuration is evaluated using an energy function. High gradient magnitudes along the border of the ellipse are favored and overlapping ellipses are penalized. Reversible Jump Markov Chain Monte Carlo sampling in combination with simulated annealing provides the global energy optimum, which describes the conformance with a predefined model. For generating the impact map a probability map is defined which is created from the automatic detections via kernel density estimation. By setting a threshold, areas around the detections are classified as contaminated or uncontaminated sites, respectively. Our results show the general potential of the method for the automatic detection of bomb craters and its automated generation of an impact map in a heterogeneous image stock.

AB - The aftermath of wartime attacks is often felt long after the war ended, as numerous unexploded bombs may still exist in the ground. Typically, such areas are documented in so-called impact maps which are based on the detection of bomb craters. This paper proposes a method for the automatic detection of bomb craters in aerial wartime images that were taken during the Second World War. The object model for the bomb craters is represented by ellipses. A probabilistic approach based on marked point processes determines the most likely configuration of objects within the scene. Adding and removing new objects to and from the current configuration, respectively, changing their positions and modifying the ellipse parameters randomly creates new object configurations. Each configuration is evaluated using an energy function. High gradient magnitudes along the border of the ellipse are favored and overlapping ellipses are penalized. Reversible Jump Markov Chain Monte Carlo sampling in combination with simulated annealing provides the global energy optimum, which describes the conformance with a predefined model. For generating the impact map a probability map is defined which is created from the automatic detections via kernel density estimation. By setting a threshold, areas around the detections are classified as contaminated or uncontaminated sites, respectively. Our results show the general potential of the method for the automatic detection of bomb craters and its automated generation of an impact map in a heterogeneous image stock.

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KW - RJMCMC

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