Automatic vehicle detection using spaceborne optical remote sensing images in city area
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Abstract
It is difficult to detect vehicles in city area by using paceborne optical remote sensing images, because the background in city area is too complex. In this paper, an automatic vehicle detection method was proposed to address the issue by using background segmentation method. Firstly, the physical property of the vegetation was analyzed and used to suppress the vegetation background of a scene by using the multi- spectral information of the scene. Next, the reflectance characteristics of city area cover types were analyzed. Based on the reflectance characteristics of building roofs and roads, the building background in the scene was removed by employing the binary morphological method on the panchromatic band image. Finally, the famous RX algorithm was introduced to detect the vehicles on the vegetation and building background suppressed image. The proposed method is applied to the actual Quickbird image for vehicle target detection. The results show that the proposed method has strong robustness, high efficiency, and automatic characteristics, and can be used for vehicle detection in city area.
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