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Salient man-made object detection based on saliency potential energy for unmanned aerial vehicles remote sensing image

机译:基于显着潜力能量的突出人为对象检测无人机遥感图像

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摘要

It is difficult to automatically recognize complex ground objects, and massive data images with the super-high ground resolution in images captured by unmanned aerial vehicles (UAVs). In order to directly identify the salient man-made ground objects from the UAV remote sensing (RS) image, a saliency detection method based on saliency potential energy (SPE) is proposed. With a detection, filtration and backtracking strategy, the texture, shape and colour of the UAV RS image are comprehensively and numerally analysed by the SPE to detect the salient man-made objects. Both qualitative and quantitative evaluations have indicated that, compared to the state-of-art saliency detection methods, our method could achieve better performance with better accuracy and less errors, which prove that our method has great application potential in UAV RS image understanding.
机译:难以自动识别复杂的地面对象,以及具有由无人机飞行器(UAV)捕获的图像中的超高接地分辨率的大规模数据图像。 为了直接从UAV遥感(RS)图像中识别突出的人工地面对象,提出了一种基于显着势能(SPE)的显着性检测方法。 通过检测,过滤和回溯策略,通过SPE综合地和数量地分析UAV RS图像的纹理,形状和颜色以检测突出的人造物体。 定性和定量评估表明,与最先进的显着性检测方法相比,我们的方法可以通过更好的准确度和更少的错误来实现更好的性能,证明我们的方法在UAV RS图像中具有很大的应用潜力。

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