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近年来,随着我国航天领域的飞速发展,不断有光学卫星传回的高分辨率的影像数据。高分辨率影像数据内数据挖掘成为深入研究相关领域的重要方法。传统卫星影像数据挖掘方法存在影像数据内容分析准确度低、影像数据内容关联信息少、处理速度慢等问题。为此,提出分布式环境下高分辨率光学卫星影像数据挖掘方法。采用动态图像特征检索算法、大数据动态信息交互技术与分布式影像数据处理技术,针对性解决传统影像数据挖掘方法中存在的问题。仿真实验测试证明,提出的分布式环境下高分辨率光学卫星影像数据挖掘方法具有影像数据加载分析快、数据挖掘准确、挖掘数据实用性高等特点。
In recent years, with the rapid development of China’s aerospace field, there are constantly high-resolution image data returned by optical satellites. Data mining in high-resolution image data has become an important method for further research in related fields. Traditional satellite image data mining methods have the problems of low accuracy of image data analysis, less information related to image data, and slow processing speed. Therefore, a high resolution optical satellite image data mining method in distributed environment is proposed. It adopts dynamic image feature retrieval algorithm, big data dynamic information interaction technology and distributed image data processing technology to solve the problems existing in traditional image data mining methods. The simulation experiments show that the proposed high-resolution optical satellite image data mining method in distributed environment has the advantages of fast loading and analysis of image data, accurate data mining and high practicability of data mining.