@inproceedings{f98c4a1c97cd4247849b6eb28166dff5,
title = "Coupled hyperspectral super-resolution and unmixing",
abstract = "The acquired hyperspectral data are always in low resolution in both spatial and spectral domains, which will result in lots of mixed pixels and degrade the detection and recognition performance in civil and military applications. So many super resolution techniques are applied to overcome this limit. In this paper, we propose a coupled hyperspectral spatial super-resolution and spectral unmixing method based on sparse representation. Combing spatial super-resolution and spectral unmixing can precisely conserve both spatial information and spectral correlation among different bands. Spectral unmixing is taken as a regularization term in spatial super-resolution to test spectral consistency and avoid spectral distortion, while spatial super-resolution is used to enhance the resolution of abundance map after spectral unmixing.",
keywords = "Hyperspectral, sparsity, spectral unmixing, super resolution",
author = "Yongqiang Zhao and Chen Yi and Jingxiang Yang and Chan, {Jonathan Cheung Wai}",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; Joint 2014 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2014 and the 35th Canadian Symposium on Remote Sensing, CSRS 2014 ; Conference date: 13-07-2014 Through 18-07-2014",
year = "2014",
month = nov,
day = "4",
doi = "10.1109/IGARSS.2014.6947016",
language = "英语",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2641--2644",
booktitle = "International Geoscience and Remote Sensing Symposium (IGARSS)",
}