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RECOGNITION AND DETECTION OF IMPACT CRATERS FROM EO PRODUCTS

机译:从EO产品识别和检测撞击陨石坑

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Impact craters represent a novel and fundamental field of research in Solar System studies. The quest for Earth impact craters entails the exploitation of Earth Observation products and of their processing for the identification of crater features, their detection and possible recognition. In the past decades, impacts by extraterrestrial bodies were regarded as an interesting but certainly not important phenomenon in the spectrum of geological processes affecting the dynamic evolution of the Earth. On the contrary, at the present, the attention devoted to this phenomenon is significantly increased, thanks to the important role played by planetary exploration. According to planetary scientists [1], impact cratering was a dominant geological process during the growth of the planetary bodies of the Solar System. The emerging of this kind of view of planets as geological objects, places the search for unknown impact craters as a basic element for the study of the evolution of the planets, and in particular of the Earth. In this context, this paper addresses the issue of recognition and detection of impact craters on the Earth by using Earth Observation products (I.e. remote sensing images). In particular, approaches based on the Hough Transform and on the Radial Consistency measure are considered and compared. In addition, novel techniques (based on the use of the K-means algorithm and of stochastic processes) for the reduction of the computational load associated with the considered approaches are described. Preliminary experimental results are reported that point out advantages and disadvantages of the considered methods.
机译:影响陨石坑代表太阳系研究的新颖和基本的研究领域。对地球冲击陨石坑的追求需要利用地球观测产品和它们的处理,以确定火山口特征,其检测和可能的识别。在过去几十年中,各外机构的影响被视为影响地球动态演化的地质过程的频谱中的一个有趣,但肯定并不重要。相反,目前,由于行星勘探所扮演的重要作用,致力于这种现象的注意力显着增加。根据行星科学家[1],影响陨石坑是太阳系行星体的增长过程中的主要地质过程。这种行星视野作为地质物体的新兴,将未知的冲击陨石坑作为研究的基本要素,以研究行星的演变,特别是地球。在这方面,本文通过使用地球观察产品(即遥感图像)来解决地球上的冲击陨石坑的识别和检测问题。特别地,考虑并比较了基于Hough变换和径向一致性测量的方法。另外,描述了用于减少与所考虑的方法相关的计算负载的降低计算载荷的新技术(基于K-Means算法和随机过程的使用)。报告了初步实验结果,指出了所考虑的方法的优缺点。

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