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Merkle quad-tree based remote sensing image analysis

机译：基于Merkle四叉树的遥感图像分析

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With the rapid development of remote sensing data, the instant and high-efficient analysis on remote sensing image become a challenge. In our research, we adopt the main idea of Merkle Tree and incorporate it with the regular quad-tree to generate an advanced Merkle Quad-Tree structure to assist the remote sensing image analysis. A series of experiments are conducted to authenticate the advantages of the proposed method. In the experiment, the remote sensing images from “Beijing 1” Micro-satellite Image in 2015 are modified on a different level to examine the comparison time consuming for various methods. It turns out that the Merkle Quad-Tree assisting method exhibits stable advantages with the different levels of modifications and which is around 1 percent of the time consumption of the traditional method. The considerable improvements seem to come primarily from the data-mapping process which results in a small and fixed data size.
机译：随着遥感数据的迅速发展，对遥感图像进行即时，高效的分析成为一个挑战。在我们的研究中，我们采用Merkle Tree的主要思想，并将其与常规四叉树合并以生成高级的Merkle Quad-Tree结构，以协助进行遥感图像分析。进行一系列实验以验证所提出方法的优点。在实验中，对2015年“北京1号”微卫星图像的遥感图像进行了不同程度的修改，以检验各种方法的比较耗时。事实证明，梅克尔四叉树辅助方法在不同的修改级别上均显示出稳定的优势，大约是传统方法所耗时间的1％。相当大的改进似乎主要来自数据映射过程，该过程导致了较小且固定的数据大小。

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