Hyperspectral Band Selection based on Improved Affinity Propagation
| dc.contributor.author | Zhu, Qingyu | |
| dc.contributor.author | Wang, Yulei | |
| dc.contributor.author | Wang, Fengchao | |
| dc.contributor.author | Song, Meiping | |
| dc.contributor.author | Chang, Chein-I | |
| dc.date.accessioned | 2021-06-14T21:06:33Z | |
| dc.date.available | 2021-06-14T21:06:33Z | |
| dc.date.issued | 2021 | |
| dc.description | 11 Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS) 2021 | en_US |
| dc.description.abstract | Dimensionality reduction is a common method to reduce the computational complexity of hyperspectral images and improve the classification performance. Band selection is one of the most commonly used methods for dimensionality reduction. Affinity propagation (AP) is a clustering algorithm that has better performance than traditional clustering methods. This paper proposes an improved AP algorithm (IAP), which divides each intrinsic cluster into several subsets, and combines the information entropy to change the initial availability matrix to obtain a suitable number of clustering results with arbitrary shapes. The experimental results on the public hyperspectral data set show that the band combination selected by IAP has a better classification accuracy compared with all bands data set and band subset by traditional AP algorithm. | en_US |
| dc.description.sponsorship | This work is supported by the National Nature Science Foundation of China (61801075), China Postdoctoral Science Foundation (No. 2020M670723), Open Research Funds of State Key Laboratory of Integrated Services Networks, Xidian University (N0. ISN20-15) and the Fundamental Research Funds for the Central Universities (3132019341). | en_US |
| dc.description.uri | http://www.ieee-whispers.com/wp-content/uploads/2021/03/WHISPERS_2021_paper_21.pdf | en_US |
| dc.format.extent | 4 pages | en_US |
| dc.genre | conference papers and proceedings preprints | en_US |
| dc.identifier | doi:10.13016/m2stlx-ftfo | |
| dc.identifier.citation | Zhu, Qingyu et al; Hyperspectral Band Selection based on Improved Affinity Propagation; 11 Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS) 2021; http://www.ieee-whispers.com/wp-content/uploads/2021/03/WHISPERS_2021_paper_21.pdf | en_US |
| dc.identifier.uri | http://hdl.handle.net/11603/21742 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | IEEE | en_US |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department Collection | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | |
| dc.title | Hyperspectral Band Selection based on Improved Affinity Propagation | en_US |
| dc.type | Text | en_US |