@inproceedings{71fc58775f97495e85566c285e2e24d4,
title = "Selecting band subsets from hyperspectral image through a novel evolutionary-based strategy",
abstract = "Hyperspectral dimensionality reduction by optimal band selection attracts wide attention recently because a few pivotal and physically meaningful bands can not only represent the whole image cube without losing effectiveness but also mitigate the computational burden. In this paper, we construct an efficient searching strategy based on the clonal selection principle to optimize a geometry-based criterion named maximum ellipsoid volume (MEV). The main contributions are two-fold: 1) a subtle relationship that can accelerate the calculation of the criterion and 2) an evolutionary strategy to relieve the heavy computational burden of obtaining the desired bands from numerous quality candidates. The experimental result on a real hyperspectral data demonstrates that the proposed method is effective.",
keywords = "Band selection, Clonal selection principle, Hyperspectral image, Maximum ellipsoid volume",
author = "Xuefeng Jiang and Lin Zhang and Fahong Zhang and Junrui Liu and Qi Wang",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE; 38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 ; Conference date: 22-07-2018 Through 27-07-2018",
year = "2018",
month = oct,
day = "31",
doi = "10.1109/IGARSS.2018.8517879",
language = "英语",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4697--4700",
booktitle = "2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings",
}