Enhanced multidimensional field embedding method by potential fields for hyperspectral image classification and visualisation
Yazarlar (2)
Doç. Dr. Caner ÖZCAN Karabük Üniversitesi, Türkiye
O. Ersoy
College of Engineering, Amerika Birleşik Devletleri
College of Engineering, Amerika Birleşik Devletleri
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Electronics Letters (Q3) | ||
| Dergi ISSN | 0013-5194 Dergi Bilgileri (2018) | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 06-2018 |
| Kabul Tarihi | – | Yayınlanma Tarihi | 01-06-2018 |
| Cilt / Sayı / Sayfa | 54 / 12 / 756–758 | DOI | 10.1049/el.2018.0676 |
| Makale Linki | https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/el.2018.0676 | ||
| UAK Araştırma Alanları |
Görüntü İşleme
|
||
| 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 | |
| Web of Science | 1 |
| Scopus | 1 |
| Google Scholar | 3 |