Enhanced multidimensional field embedding method by potential fields for hyperspectral image classification and visualisation
Yazarlar (2)
Doç. Dr. Caner ÖZCAN
Karabük Üniversitesi, Türkiye
College Of Engineering, Amerika Birleşik Devletleri
| Makale Türü | Özgün Makale |
| Makale Alt Türü | SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale |
| Dergi Adı | Electronics Letters |
| Dergi ISSN | 0013-5194 Wos Dergi Scopus Dergi |
| Dergi Tarandığı Indeksler | SCI-Expanded |
| Dergi Grubu | Q4 |
| Makale Dili | İngilizce |
| Basım Tarihi | 06-2018 |
| Cilt No | 54 |
| Sayı | 12 |
| Sayfalar | 756 / 758 |
| DOI Numarası | 10.1049/el.2018.0676 |
| Makale Linki | https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/el.2018.0676 |
| Özet |
| Multidimensional field embedding methods have been demonstrated to effectively characterise spectral signatures in hyperspectral images. However, high-dimensional data composed of a number of classes presents challenges to the existing embedding methods. This Letter proposes an enhanced multidimensional field embedding algorithm based on the force field formulation. The comparative performance of the proposed algorithm is evaluated in the classification and visualisation of commonly used hyperspectral images. Experimental results demonstrate its superiority over previously used field embedding techniques. |
| Anahtar Kelimeler |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| WoS | 1 |
| SCOPUS | 1 |
| Google Scholar | 3 |