@inproceedings{6abb71fbdab04d6c8b4c3baca39457f7,
title = "Nonlocal similarity regularization for sparse hyperspectral unmixing",
abstract = "This paper is concerned with semisupervised hyperspectral unmixing using a nonlocal similarity prior on the abundance images. To this end, the nonlocal self-similarity regularization is incorporated into the classical sparse regression formula to propose a new model for hyperspectral sparse unmixing. The rationale is the idea that there are many nonlocal similar patches to the given patch in the abundance images. The effectiveness of the proposed algorithm is illustrated using the synthetic and real data sets.",
keywords = "Hyperspectral remote sensing, nonlocal similarity regularization, sparse unmixing, spectral library",
author = "Rui Wang and Li, {Heng Chao}",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; null ; Conference date: 13-07-2014 Through 18-07-2014",
year = "2014",
month = nov,
day = "4",
doi = "10.1109/IGARSS.2014.6947089",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2926--2929",
booktitle = "International Geoscience and Remote Sensing Symposium (IGARSS)",
}