@inproceedings{3e50144c03184dd2861f76eb9d302282,
title = "Joint supervised-unsupervised nonlinear unmixing of hyperspectral images using kernel method",
abstract = "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.",
keywords = "Coherence Criterion, Hyperspctral Image, Joint Supervised-unspervised Method, Kernel Method, Nonlinear Unmixing",
author = "Hong Xiao and Hui Liu and Jie Chen",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 5th International Conference on Intelligent Systems Design and Engineering Applications, ISDEA 2014 ; Conference date: 15-06-2014 Through 16-06-2014",
year = "2014",
month = dec,
day = "4",
doi = "10.1109/ISDEA.2014.136",
language = "英语",
series = "Proceedings - 2014 5th International Conference on Intelligent Systems Design and Engineering Applications, ISDEA 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "582--585",
booktitle = "Proceedings - 2014 5th International Conference on Intelligent Systems Design and Engineering Applications, ISDEA 2014",
}