A label propagation method using spatial-spectral consistency for hyperspectral image classification
Haichang Li; Ying Wang; Shiming Xiang; Jiangyong Duan; Feiyun Zhu; Chunhong Pan; haichang516@gmail.com
2016-01-04
发表期刊International Journal of Remote Sensing
卷号37期号:1页码:191-211
摘要
In this article, a label propagation approach with automatic seed selection is developed for hyperspectral image classification. The core idea is to combine pixel-wise classification results with spatial information described by a data graph. Using only the support vector machine (SVM) classifier on spectral features to tackle the hyperspectral classification task will produce results with a salt and pepper appearance. To overcome this limitation, the spatial information is incorporated by label propagation. The performance of label propagation is dependent on two points: the seeds and the connection graph. Generally, a limited number of labelled samples are available, which are considered as seeds in label propagation. However, the limited seeds will result in bad label propagation. Therefore, pseudo-seeds are automatically selected in local windows. Specifically, the pixels whose initial labels according to SVM are consistent with their most spatial neighbours are selected as seeds. Through seed selection, the number of seeds is greatly increased. Then, the label information of the selected seeds is propagated to their spatial neighbours using a data graph which is constructed according to the local structures in the image. Through seed selection and label propagation
on the graph, the problem of salt-and-pepper appearance is solved elegantly – the noisy labels are highly suppressed and most of the structures are preserved. Competitive experimental results on a variety of hyperspectral data sets demonstrate the effectiveness of the proposed method.
关键词Hyperspectral Image Classification Label Propagation Spatial-spectral.
WOS研究方向Remote Sensing ; Image Science & Photographic Technology
WOS类目Remote Sensing ; Image Science & Photographic Technology
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/11123
专题模式识别国家重点实验室_先进数据分析与学习
通讯作者haichang516@gmail.com
作者单位National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences
推荐引用方式
GB/T 7714
Haichang Li,Ying Wang,Shiming Xiang,et al. A label propagation method using spatial-spectral consistency for hyperspectral image classification[J]. International Journal of Remote Sensing,2016,37(1):191-211.
APA Haichang Li.,Ying Wang.,Shiming Xiang.,Jiangyong Duan.,Feiyun Zhu.,...&haichang516@gmail.com.(2016).A label propagation method using spatial-spectral consistency for hyperspectral image classification.International Journal of Remote Sensing,37(1),191-211.
MLA Haichang Li,et al."A label propagation method using spatial-spectral consistency for hyperspectral image classification".International Journal of Remote Sensing 37.1(2016):191-211.
条目包含的文件 下载所有文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
Haichang Li.pdf(3399KB)期刊论文作者接受稿开放获取CC BY-NC-SA浏览 下载
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Haichang Li]的文章
[Ying Wang]的文章
[Shiming Xiang]的文章
百度学术
百度学术中相似的文章
[Haichang Li]的文章
[Ying Wang]的文章
[Shiming Xiang]的文章
必应学术
必应学术中相似的文章
[Haichang Li]的文章
[Ying Wang]的文章
[Shiming Xiang]的文章
相关权益政策
暂无数据
收藏/分享
文件名: Haichang Li.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。