Hyperspectral Classification of Clustering SVM Based on Modified Spatial Information

摘要：

　　The difference in local spectral bands of the same species and the local spectral similarity between different species can easily lead to the occurrence of noise points in the region in the traditional classification results.The multi-spectral gray image weighting and the overall gray image weighting filtering algorithm are used to improve the image texture feature,and the modified image is used to perform small window clustering classification based on the high confidence class pixel.The results show that the classification model of the improved algorithm has a certain improvement in classification accuracy: it is 12.3%higher than the traditional SVM classification,and the image noise phenomenon is obviously improved.

关键词： Spatial correction Hyperspectral Vegetation classification CSVM Weighted filtering

作者: Feng-lian LIU Chi WU Chen ZHAO Yong-xing CAO Zhi-hang XUE

作者单位: State Grid Sichuan Electric Power Research Institute,Chengdu 610072,China School of Electrical Engineering,Southwest Jiaotong University,Chengdu 611756,China

会议类型: 国际会议

会议名称: 2019 International Conference on Informatics, Control and Robotics 2019信息学、控制和机器人学国际会议(ICICR2019)

会议地点: 上海

会议语种:英文

页码: 201-205

在线出版日期: 2019-06-16（万方平台首次上网日期，不代表论文的发表时间）