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Change Detection in Aerial Images Using Three-Dimensional Feature Maps
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.ORCID iD: 0000-0002-6643-312x
2020 (English)In: Remote Sensing, ISSN 2072-4292, E-ISSN 2072-4292, Vol. 12, no 9, article id 1404Article in journal (Refereed) Published
Abstract [en]

 Interest in aerial image analysis has increased owing to recent developments in and availabilityofaerialimagingtechnologies,likeunmannedaerialvehicles(UAVs),aswellasagrowing need for autonomous surveillance systems. Variant illumination, intensity noise, and different viewpointsareamongthemainchallengestoovercomeinordertodeterminechangesinaerialimages. In this paper, we present a robust method for change detection in aerial images. To accomplish this, the method extracts three-dimensional (3D) features for segmentation of objects above a defined reference surface at each instant. The acquired 3D feature maps, with two measurements, are then used to determine changes in a scene over time. In addition, the important parameters that affect measurement, such as the camera’s sampling rate, image resolution, the height of the drone, and the pixel’sheightinformation,areinvestigatedthroughamathematicalmodel. Toexhibititsapplicability, the proposed method has been evaluated on aerial images of various real-world locations and the results are promising. The performance indicates the robustness of the method in addressing the problems of conventional change detection methods, such as intensity differences and shadows.

Place, publisher, year, edition, pages
2020. Vol. 12, no 9, article id 1404
Keywords [en]
aerial images; 3D change detection; optical vehicle surveillance; remote sensing; unmanned aerial vehicle
National Category
Signal Processing Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:bth-19422DOI: 10.3390/rs12091404OAI: oai:DiVA.org:bth-19422DiVA, id: diva2:1427772
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open access

Available from: 2020-05-01 Created: 2020-05-01 Last updated: 2020-05-04Bibliographically approved

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Javadi, Mohammad SalehDahl, MattiasPettersson, Mats

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7891011121310 of 18
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