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元胞自动机的遥感影像混合像元分类
引用本文:王旭红,郭建明,贾百俊,张宇坤.元胞自动机的遥感影像混合像元分类[J].测绘学报,2008,37(1):42-48.
作者姓名:王旭红  郭建明  贾百俊  张宇坤
作者单位:西北大学城市资源学系,陕西西安,710069;西北大学城市资源学系,陕西西安,710069;西北大学城市资源学系,陕西西安,710069;西北大学城市资源学系,陕西西安,710069
基金项目:陕西省自然科学基金 , 两北大学校内基金 , 西北大学校内基金科研启动基金 , 国家测绘科技发展基金
摘    要:通过对元胞自动机理论的研究,提出元胞自动机的遥感影像混合像元分解模型。利用多波段遥感数据验证混合像元分解算法的可行性,并将结果与线性分解模型进行比较。结果表明,元胞自动机混合像元分解模型在分解的准确性方面,明显优于一般线性模型的精度。最后,将分类结果与传统的监督分类算法比较,得出元胞自动机的混合像元分解模型明显优于监督分类精度的结论。

关 键 词:遥感影像  空间相关性  元胞自动机  混合像元分解  分类
文章编号:1001-1595(2008)01-0042-07
收稿时间:2006-11-14
修稿时间:2007-09-28

Mixed Pixels Classification of Remote Sensing Images Based on Cellular Automata
WANG Xu-hong,GUO Jian-ming,JIA Bai-jun,ZHANG Yu-kun.Mixed Pixels Classification of Remote Sensing Images Based on Cellular Automata[J].Acta Geodaetica et Cartographica Sinica,2008,37(1):42-48.
Authors:WANG Xu-hong  GUO Jian-ming  JIA Bai-jun  ZHANG Yu-kun
Abstract:By means of cellular automata, a new scheme for detection and classification of sub-pixel in remote sensing images is presented. In this study, experiments which the mixed pixels were assigned several land cover classes according to the new proposed algorithms by using multi-channel remote sensing images data is proved feasible. Comparison of the proposed scheme with Linear-model were performed. The results show that the accuracy of proposed scheme is obviously higher than general linear-model's. At last, the result comparing mixed pixels classification by using cellular automata with traditional supervised classification algorithms proves that the new scheme can get more accurate estimates of land cover.
Keywords:remote sensing image  spatial correlation  cellular automata  mixed pixels decomposition  classification
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