摘要
为了提高遥感图像检索的准确性,提出了一种基于人工免疫系统(artificial immune system)的遥感图像检索算法。该算法根据相关反馈技术及免疫机理,利用克隆选择算法对用户反馈的图像特征进行泛化学习,从而提高了系统对用户语义的理解能力。实验结果表明,该算法能有效理解用户的反馈信息,能提高检索的准确性。
A novel remote sensing image retrieval method based on artificial immune system（AIS） is proposed in this paper.Based on the relevance feedback technology and immune mechanism,clonal selection algorithm is used to learn and memorize the user feedback image feature,the recognition of customers＇ semantic target for system is improved.Experimental results show that this approach can recognize the user feedback information efficiently and improve the retrieval accuracy.
出处
《北京测绘》
2011年第2期7-11,共5页
Beijing Surveying and Mapping
关键词
人工免疫系统
遥感图像检索
相关反馈
克隆选择
artificial immune system
remote sensing image retrieval
relevance feedback
clonal selection
