The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B2-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 1195–1202, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1195-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2020, 1195–1202, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B2-2020-1195-2020

  14 Aug 2020

14 Aug 2020

TOWARDS DETECTION OF THERMAL ANOMALIES IN LARGE URBAN AREAS USING SIMULATION

E. Burkard1, D. Bulatov1,2, and B. Kottler1 E. Burkard et al.
  • 1Fraunhofer IOSB, Gutleuthausstrasse 1, 76275 Ettlingen, Germany
  • 2Curtin University of Technology, Department of Spatial Sciences, GPO Box U1987, Perth, WA 6845, Australia

Keywords: Thermal Simulation, Anomaly Detection, Change Detection, Infrared Imagery

Abstract. Anomaly detection in imagery has widely been studied and enhanced towards the requirements of today’s available sensor data, whereas many of them require a background estimation in order to identify an anomaly or target. In this paper, we examine an analysis of simulation as background estimator for anomaly detection in thermal images of urban sceneries. We generate a surface temperature image and a sensor-like infrared image by combined image and elevation data and a thermal model suited for large scenes and fast simulation. With the simulated thermal image, we define anomalies as deviation between measurement and simulation. Pixel-wise image differencing of the measured and simulated temperatures and infrared images respectively are performed and evaluated concerning the full images as well as class-wise, including a material classification of the observed area. Our approach shows complementary results compared to RXD application on the measured infrared images. Metal roofs which appear warm in the thermal image and are not visually distinguishable from the residual image are detected.