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A Novel Multi-radius Neighborhood Rough Set Weighted Feature Extraction Method for Remote Sensing Image Classification
其他题名适用于遥感分类的多邻域粗糙集加权特征提取方法
Chen Tieqiao1,2,3; Liu Jiahang1; Zhu Feng1,2,3; Wang Yihao1; Liu Jia1; Chen Jie4
作者部门遥感与智能信息系统研究中心
2018-02
发表期刊Geomatics and Information Science of Wuhan University
ISSN1671-8860
卷号43期号:2页码:311-317
产权排序1
摘要

The neighborhood rough set model can be effective for keeping or even improving classification accuracy.This model however,still has some disadvantages as it has low stability in classification precision,requires repeated neighborhood radius adjustments,and cannot realize automatic feature extraction.In order to solve these problems,this paper presents a multi-radius neighborhood rough set weighted feature extraction method for high resolution remote sensing image classification.The neighborhood rough set model was used to extract texture and spectrum features of image by setting gradually increasing radius with equally spaced steps,as a result effective subset features under different radius were obtained.The presence probablity of each feature under all the different radius was calculated,each feature was endowed with weight by its presence probability,so the final weighted features of image were acquired.The newly obtained features were applied to image classification using a support vector machine.Experiments on QuickBird images demonstrate that the proposed method can provide better classification results.Compared with other state-off-art neighborhood rough set model with effective radius,the overall accuracy exceeded about 3.88% while the Kappa coefficient exceeded about 5.16%.A classification experiment on a GeoEye-1 image also showed the effectiveness of the proposed method.All the classification experiment results show that the proposed method can improve classification precision and automation of high resolution remote sensing images.

关键词Neighborhood Rough Set Model Multi-radius Neighborhood Rough Set Feature Extraction High Spatial Resolution Remote Sensing Image Object-oriented Classification
学科领域Geology
DOI10.13203/j.whugis20150290
收录类别EI ; CSCD
语种中文
EI入藏号20182105230929
引用统计
文献类型期刊论文
条目标识符http://ir.opt.ac.cn/handle/181661/30097
专题遥感与智能信息系统研究中心
通讯作者Liu Jiahang
作者单位1.Xi'an Institute of Optics and Precision Mechanics of CAS, Xi'an, 710119, China
2.University of Chinese Academy of Sciences, Beijing, 100049, China
3.Key Laboratory of Lunar and Deep Space Exploration, Beijing 1000012, China
4.Department of Geo-informatics, Central South University, Changsha 410083, China
推荐引用方式
GB/T 7714
Chen Tieqiao,Liu Jiahang,Zhu Feng,et al. A Novel Multi-radius Neighborhood Rough Set Weighted Feature Extraction Method for Remote Sensing Image Classification[J]. Geomatics and Information Science of Wuhan University,2018,43(2):311-317.
APA Chen Tieqiao,Liu Jiahang,Zhu Feng,Wang Yihao,Liu Jia,&Chen Jie.(2018).A Novel Multi-radius Neighborhood Rough Set Weighted Feature Extraction Method for Remote Sensing Image Classification.Geomatics and Information Science of Wuhan University,43(2),311-317.
MLA Chen Tieqiao,et al."A Novel Multi-radius Neighborhood Rough Set Weighted Feature Extraction Method for Remote Sensing Image Classification".Geomatics and Information Science of Wuhan University 43.2(2018):311-317.
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