结合粗糙集理论和遥感数据中地物光谱特征空间分布信息，提出了一种基于光谱特征邻域的容差粗糙集分类方法，用来处理卫星遥感数据分类中的不确定性问题。
Based on the spectral feature neighborhood, this paper proposes a tolerant rough set classification method to handle the uncertainty in the process of satellite remote sensing data classification.
通过实例比较，说明本方法应用于大气遥感红外光谱数据的分类和识别时，是行之有效的。
Experimental results show that this method is more effective than local search on identification and classfication of gas's infrared remote sensing data.
摘要基于独特型免疫网络原理，提出了一种新型的分区记忆模式人工独特型网络模型，并利用其对卫星遥感数据进行了分类。
Based on idiotypic immune network theory, a Regional-memory-pattern Artificial idiotypic network (RAIN) is proposed to classify multi-spectral remote sensing image.
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