Knowledge driven change detection method for aircraft targets

doi:10.6046/gtzyyg.2016.04.12

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Abstract

Aimed at high-resolution optical sense images, this paper proposes a knowledge driven change detection method for the aircraft targets. First, a spatial mask image of the airport is set up according to the geographical position information and the candidate area of aircraft targets is obtained. Second, the control points' information in the target area is utilized to register input images. As changes of aircraft targets can lead to significant texture changes in area, the authors detected the changes by extracting texture features. A weak texture elimination and edge suppression method was put forward to reduce the false-alarm rate. Finally, the mathematical morphological operation method was employed to eliminate some isolation points and acquire the detection results. Experiments show that the proposed method can efficiently reduce the false-alarm caused by registration error and skirt response, with the detection rate of aircraft targets reaching 92.47%.

Keywords UAV object-oriented segmentation mean shift information extraction

TP751.1

Issue Date: 20 October 2016

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	HU Yong
	ZHANG Xiaocheng
	MA Zezhong
	ZHOU Zhiyue

Cite this article:

HU Yong,ZHANG Xiaocheng,MA Zezhong, et al. Knowledge driven change detection method for aircraft targets[J]. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(4): 77-82.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2016.04.12 OR https://www.gtzyyg.com/EN/Y2016/V28/I4/77

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