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Research on Retrieval of Remote Sensing Images based on Shape Feature

机译:基于形状特征的遥感影像检索研究

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摘要

How to recognize man-made objects from high-resolution remote sensing images has been considered an attractive and important research field in remote sensing applications undoubtedly. In this paper we try to present a feasible contour-based retrieval strategy of remote sensing images. The merit of our strategy is it can avoid the impact caused by the difficult of automatic manmade object discrimination so far and the deficiency of huge computational volume aroused by template matching. Besides, on the basis of analyzing the limitations of common descriptors such as Fourier descriptor and Hu invariant moments, invariant relative moments are adopted to describe shape feature of man-made objects in our retrieval strategy. After describing contour feature extraction method, feature matching method and retrieval process based on shape feature, a prototype system is also designed and implemented to prove the validity and accuracy of our strategy mentioned above. In our experiments three types of man-made objects with different shape feature, i.e., boat, oilcan and buildings with flat-roof, are selected as our research targets. Experimental results illustrate that our strategy is feasible and the corresponding retrieval performance is analyzed, followed by conclusions and future works.
机译:毫无疑问,如何从高分辨率遥感图像中识别人造物体已被认为是遥感应用领域中一个有吸引力且重要的研究领域。在本文中,我们尝试提出一种可行的基于轮廓的遥感图像检索策略。我们的策略的优点是可以避免迄今为止由于人工目标的自动识别困难而造成的影响,以及模板匹配引起的巨大计算量的不足。此外,在分析常用的傅立叶描述符和Hu不变矩等描述符的局限性的基础上,在我们的检索策略中采用不变相对矩来描述人造物体的形状特征。在描述轮廓特征提取方法,特征匹配方法和基于形状特征的检索过程之后,还设计并实现了原型系统,以证明上述策略的有效性和准确性。在我们的实验中,我们选择了三种具有不同形状特征的人造物体,即船,油罐和具有平屋顶的建筑物作为我们的研究对象。实验结果表明,该策略是可行的,并对相应的检索性能进行了分析,然后得出结论和今后的工作。

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