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Aircraft Recognition in High-Resolution Optical Satellite Remote Sensing Images

机译:高分辨率光学卫星遥感影像中的飞机识别

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摘要

Automatic aircraft recognition is a challenging task. Conventional methods always extract the overall shapes of aircraft at first and then represent the aircraft based on the extracted shape with different features for recognition. The major problem of these methods is that they have a high requirement on shape extraction, which is too idealistic for targets in satellite images. In this letter, we propose a new aircraft recognition approach that can recognize aircraft robustly without perfect extraction of silhouette or shape of aircraft as a precondition, and can deal with the situation of parts missing and shadow disturbance. Specifically, a direction estimation method is proposed first to align aircraft to a same direction. Then, a reconstruction-based similarity measure is proposed, which transforms the type recognition problem into a reconstruction problem. Finally, a jigsaw matching pursuit algorithm is proposed to solve the reconstruction problem. We use panchromatic Quickbird imagery for evaluation, and the experimental results illuminate that the proposed method is effective and accurate.
机译:自动飞机识别是一项艰巨的任务。常规方法总是首先提取飞机的总体形状,然后基于所提取的具有不同特征的形状来表示飞机以进行识别。这些方法的主要问题是它们对形状提取有很高的要求,这对于卫星图像中的目标来说太理想了。在这封信中,我们提出了一种新的飞机识别方法,该方法可以在不完美提取飞机轮廓或形状的前提下可靠地识别飞机,并且可以处理零件丢失和阴影干扰的情况。具体而言,首先提出了一种方向估计方法,以将飞机对准同一方向。然后,提出了一种基于重构的相似性度量,将类型识别问题转化为重构问题。最后,提出了一种拼图匹配追踪算法来解决重建问题。我们使用全色Quickbird图像进行评估,实验结果表明该方法是有效且准确的。

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