Remote Sensing Classification Based on Hybrid Multi-classifier Combination Algorithm

摘要：

To improve the precision of remote sensing image classification, hybrid multi-classifier combination method is proposed. Taking the characteristic of abstract level and measurement level into consideration, the optimal sub-classifier, bagging algorithm and the most large confidence algorithm are combined. By using this model, respective advantages of different sub-classifiers are gathered. This method used in Beijing-1 and ETM image classification shows a better enhancement, and also results indicate that the hybrid multi-classifier combination algorithm is an effective algorithm for medium-high precision remote sensing image classification.

作者: YANG Haibo Zhao Hongling WANG Zongmin

作者单位: The Henan Provincial Key Lab on Information Network, Zhengzhou University, Zhengzhou 450001,China ;School of water conservancy and environment engineering, Zhengzhou University, Zhengzhou 450001,China

会议类型: 国际会议

会议名称: 第十届中国虚拟现实年会

会议地点: 上海

会议语种:英文

页码: 1688-1692

在线出版日期: 2010-10-20（万方平台首次上网日期，不代表论文的发表时间）