@inproceedings{e9ca2e1adb854c898a2ef2c81e0d405f,
title = "Hyperspectral and multispectral image fusion using CNMF with minimum endmember simplex volume and abundance sparsity constraints",
abstract = "Hyperspectral (HS) remote sensing image with finer spectral information has great advantages in feature identification and classification. However, the spatial resolution of HS image is usually low due to practical limitations. In this paper, the low-spatial-resolution HS image is fused with the high-spatial-resolution multispectral (MS) image of the same observation scene to improve its spatial resolution. A novel spectral unmixing based HS and MS image fusion approach (VSC-CNMF) is proposed, in which CNMF with minimum endmember simplex volume and abundance sparsity constraints is employed for coupled unmixing of HS and MS images. Simulative experiments are employed for verification and comparison. The experimental results illustrate that the newly proposed VSC-CNMF based HS and MS fusion algorithm outperforms several state-of-the-art unmixing based fusion approaches in cases with moderate number of endmembers.",
keywords = "Hyperspectral, image fusion, simplex volume, spasity, unmixing",
author = "Yifan Zhang and Yakun Wang and Yang Liu and Chuwen Zhang and Mingyi He and Shaohui Mei",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 ; Conference date: 26-07-2015 Through 31-07-2015",
year = "2015",
month = nov,
day = "10",
doi = "10.1109/IGARSS.2015.7326172",
language = "英语",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1929--1932",
booktitle = "2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings",
}