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利用决策级融合进行遥感影像分类
Classification for Remote Sensing Data with Decision Level Fusion
【摘要】 提出了一种基于决策级融合的遥感影像分类方法。该方法对遥感影像特征以最大似然分类器进行预分类,应用Adaboost算法将分类的结果进行决策级融合,实现影像的分类。实验结果表明,该方法的分类精度较传统分类方法有明显的提高。
【Abstract】 With the development of remote sensing technology,dealing with high-dimension features with traditional classification methods is difficult.Multiple classifiers fusion technology not only deals with high-dimension features but also improves the classification accuracies.We focuses on classifier fusion in decision level,and proposes a new classification method for remote sensing data based on Adaboost.Experiments show that this method is more effective than traditional classification algorithms.
【关键词】 决策级融合;
Adaboost;
遥感影像分类;
纹理;
【Key words】 decision level fusion; Adaboost; remote sensing data classification; texture;
【Key words】 decision level fusion; Adaboost; remote sensing data classification; texture;
【基金】 国家973计划资助项目(2007CB311003);国家自然科学基金资助项目(60875007)
- 【文献出处】 武汉大学学报(信息科学版) ,Geomatics and Information Science of Wuhan University , 编辑部邮箱 ,2009年07期
- 【分类号】P237
- 【被引频次】22
- 【下载频次】933