Merkle Quad-Tree Based Remote Sensing Image Analysis
Published in IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017
Recommended citation: Zhai Weixin, Qi Kun, Duan Jiexiong, Cheng Chengqi. Merkle quad-tree based remote sensing image analysis[C]. proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017. IEEE.
Abstract : 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.