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Fractal methods for extracting artificial objects from the unmanned aerial vehicle images

机译:从无人机图像中提取人造物体的分形方法

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Unmanned aerial vehicles (UAVs) have become used increasingly in earth surface observations, with a special interest put into automatic modes of environmental control and recognition of artificial objects. Fractal methods for image processing well detect the artificial objects in digital space images but were not applied previously to the UAV-produced imagery. Parameters of photography, on-board equipment, and image characteristics differ considerably for spacecrafts and UAVs. Therefore, methods that work properly with space images can produce different results for the UAVs. In this regard, testing the applicability of fractal methods for the UAV-produced images and determining the optimal range of parameters for these methods represent great interest. This research is dedicated to the solution of this problem. Specific features of the earth's surface images produced with UAVs are described in the context of their interpretation and recognition. Fractal image processing methods for extracting artificial objects are described. The results of applying these methods to the UAV images are presented. (C) 2016 Society of Photo-Optical Instrumentation Engineers (SPIE)
机译:无人飞行器(UAV)已越来越多地用于地表观测中,特别关注环境控制和识别人造物体的自动模式。分形图像处理方法可以很好地检测数字空间图像中的人造物体,但以前并未应用于无人机生产的图像。对于航天器和无人机,摄影参数,机载设备和图像特性存在很大差异。因此,与空间图像正确配合的方法可以为无人机产生不同的结果。在这方面,测试分形方法对无人机产生的图像的适用性并确定这些方法的最佳参数范围代表了极大的兴趣。这项研究致力于解决这个问题。无人机产生的地球表面图像的特定特征在其解释和识别的背景下进行了描述。描述了用于提取人造物体的分形图像处理方法。展示了将这些方法应用于无人机图像的结果。 (C)2016年光电仪器工程师学会(SPIE)

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