@inproceedings{f5b0fbed4c924671b015f23731edd95a,
title = "Optimal neighboring reconstruction for hyperspectral band selection",
abstract = "Band selection, as an effective and popular dimensional reduction methods for hyperspectral image (HSI), has raised wide attention in recent years. In this paper, we propose a novel band selection method called optimal neighboring reconstruction (ONR). Compared to conventional methods, ONR mainly has following advantages. 1) It is globally optimal, which means the best combination of bands towards the designed objective function can be achieved. 2) It sufficiently exploits the neighboring structure among bands, so can effectively reduce the redundancy while maintaining the discrimination among bands. Experiments on three real data sets show that the proposed method has excellent performance.",
keywords = "Band selection, Dynamic programming, Global optimal, Hyperspectral image",
author = "Fahong Zhang and Qi Wang and Xuelong Li",
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.2018.8517884",
language = "英语",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4709--4712",
booktitle = "2018 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018 - Proceedings",
}