Joint supervised-unsupervised nonlinear unmixing of hyperspectral images using kernel method

Hong Xiao, Hui Liu, Jie Chen

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

In hyper spectral images pixels are mixtures of spectral components associated to pure materials. Nonlinear unmixing of observed pixels is a challenging task in hyper spectral imagery. In this paper, a joint supervised unsupervised nonlinear unmixing scheme is proposed based on the recent advance of kernel based regression and analysis techniques. The proposed scheme takes advantage of high quality training data from the unsupervised kernel algorithm and fast learning and inference speed of the supervised learning algorithm. Experiments on synthetic and real data show the effectiveness of the proposed method.

源语言英语
主期刊名Proceedings - 2014 5th International Conference on Intelligent Systems Design and Engineering Applications, ISDEA 2014
出版商Institute of Electrical and Electronics Engineers Inc.
582-585
页数4
ISBN(电子版)9781479942619
DOI
出版状态已出版 - 4 12月 2014
已对外发布
活动2014 5th International Conference on Intelligent Systems Design and Engineering Applications, ISDEA 2014 - Zhangjiajie, Hunan, 中国
期限: 15 6月 201416 6月 2014

出版系列

姓名Proceedings - 2014 5th International Conference on Intelligent Systems Design and Engineering Applications, ISDEA 2014

会议

会议2014 5th International Conference on Intelligent Systems Design and Engineering Applications, ISDEA 2014
国家/地区中国
Zhangjiajie, Hunan
时期15/06/1416/06/14

指纹

探究 'Joint supervised-unsupervised nonlinear unmixing of hyperspectral images using kernel method' 的科研主题。它们共同构成独一无二的指纹。

引用此