基于资源限制性人工免疫系统的多光谱遥感影像分类方法
Classification of Multi-Spectral Remote Sensing Image Based on Resource Limited Artificial Immune System
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摘要: 提出了一种基于资源限制性人工免疫系统(resource limited artificial immune systems,RLAIS)的多光谱遥感影像分类方法。该方法采用RLAIS对遥感影像分类中选取的感兴趣样区进行样本训练,得到全局聚类中心,利用聚类中心对遥感影像进行分类。实验证明,该方法在分类精度上优于传统方法,其总精度和Kappa系数分别达到了91%和0.88,具有实用价值。Abstract: In this paper,some initial investigations are conducted to employ resource limited artificial immune system(RLAIS) for classification of multi-spectral remote sensing image.The proposed method trains the samples of regions of interest using the RLAIS and obtains the optimal the centers of classification.Image classification task by RLAIS is attempted and the preliminary results are provided.By the experiment,it is demonstrated that the method of this paper is superior to the three traditional algorithms,and its overall accuracy and Kappa coefficient reach 91% and 0.88 respectively.