An Automatic Accurate High-Resolution Satellite Image Retrieval Method

作     者：Fan, Zhiwei Zhang, Wen Zhang, Dongying Meng, Lingkui 

作者机构：Wuhan Univ Sch Remote Sensing & Informat Engn Wuhan 430079 Hubei Peoples R China Zhengzhou Univ Sch Water Conservancy & Environm Zhengzhou 450001 Henan Peoples R China 

出 版 物：《REMOTE SENSING》 (Remote Sens.)

年 卷 期：2017年第9卷第11期

页      面：1092-1092页

核心收录：

学科分类：0830[工学-环境科学与工程（可授工学、理学、农学学位）] 1002[医学-临床医学] 070801[理学-固体地球物理学] 07[理学] 08[工学] 0708[理学-地球物理学] 0816[工学-测绘科学与技术] 

基　　金：National Key Research and Development Program of China [2017YFC0405806] National High-Resolution Earth Observation System Projects [08-Y30B07-9001-13/15] 

主　　题：high-resolution satellite image automated retrieval method convolutional neural network geohash coding satellite image retrieval satellite image screening 

摘      要：With the growing number of high-resolution satellite images, the traditional image retrieval method has become a bottleneck in the massive application of high-resolution satellite images because of the low degree of automation. However, there are few studies on the automation of satellite image retrieval. This paper presents an automatic high-resolution satellite image accurate retrieval method based on effective coverage (EC) information, which is used to replace the artificial screening stage in traditional satellite image retrieval tasks. In this method, first, we use a convolutional neural network to extract the EC of each satellite image;then, we use an effective coverage grid set (ECGS) to represent the ECs of all satellite images in the library;finally, the satellite image accurate retrieval algorithm is proposed to complete the process of screening images. The performance evaluation of the method is implemented in three regions: Wuhan, Yanling, and Tangjiashan Lake. The large number of experiments shows that our proposed method can automatically retrieve high-resolution satellite images and significantly improve efficiency.