摘要
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。利用北京地区Landsat-5 TM数据进行分类试验,对算法分类过程进行讨论及其分类结果进行验证分析;结果表明:文中方法在可理解性和稳定性上体现出比较好的性质,能够有效处理卫星遥感数据分类中存在的不确定性因素,在具有复杂光谱特征地物分类方面具有发展潜力。
In combination of rough set theory and the distribution information of the land cover spectral feature space,a spectral feature neighborhood based tolerant rough set classification method is proposed to handle the uncertainty in the process of satellite remote sensing data classification.Experiment is carried out with Landsat-5 TM image of eastern Beijing.Working mechanism of the method is discussed and classification result is validated and analyzed.Outcome indicates that the proposed method is well interpretable and reliable,and can effectively handle the uncertainty in the process of satellite remote sensing classification.It is a promising tool at classifying areas with complex spectral feature.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第20期11-13,135,共4页
Computer Engineering and Applications
基金
国家自然科学基金(the National Natural Science Foundation of China under Grant No.40571100)
国家高技术研究发展计划(863)(the National High-Tech Research and Developm ent Plan of China under Grant No.SQ 2006AA12Z130)
关键词
卫星遥感
数据分类
光谱特征邻域
容差粗糙集
satellite remote sensing
data classification
spectral feature neighborhood
tolerant rough set