@inproceedings{8329b437c89d4f3f9754a9abf936228e,
title = "Hyperspectral image classification using multinomial logistic regression and non-local prior on hidden fields",
abstract = "In this paper, we present a supervised hyperspectral image segmentation method based on multinomial logistic regression and a convex formulation of a marginal maximum a posteriori (MAP) segmentation with non-local total variation prior on the hidden fields under Bayesian framework. It not only exploits the basic assumption that samples within each class approximately lie in a lower dimensional subspace, but also sidesteps the discrete nature of the image segmentation problems by modeling spatial prior with vectorial non local means on the hidden fields. Alternating direction method of multipliers (ADMM) is finally extended to solve the proposed model. The proposed algorithm is validated by real hyperspectral data set.",
keywords = "hidden fields, hyperspectral classification (HC), non-local total variation, sparse logistic regression",
author = "Le Sun and Shim, \{Hiuk Jae\} and Byeungwoo Jeon and Yuhui Zheng and Yunjie Chen and Liang Xiao and Zhihui Wei",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 3rd IEEE International Conference on Progress in Informatics and Computing, PIC 2015 ; Conference date: 18-12-2015 Through 20-12-2015",
year = "2016",
month = jun,
day = "10",
doi = "10.1109/PIC.2015.7489798",
language = "English",
series = "Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--4",
editor = "Liang Xiao and Yinglin Wang",
booktitle = "Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015",
}