Due to the high spectral resolution, hyperspectral images need large data storage and processing time. Indeed, its high dimensional structure requires high computational complexity, especially for target detection. In order to overcome these problems, band reduction methods have been proposed. In this paper, we compare PCA and SNR-based band reduction methods to improve target detection performance in hyperspectral images. Experimental results show that band reduction methods not only reduce processing time, but also increase accuracy rate.
Birincil Dil | İngilizce |
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Konular | Mühendislik |
Bölüm | Research Article |
Yazarlar | |
Yayımlanma Tarihi | 30 Haziran 2020 |
Gönderilme Tarihi | 16 Ocak 2020 |
Kabul Tarihi | 10 Şubat 2020 |
Yayımlandığı Sayı | Yıl 2020 Cilt: 62 Sayı: 1 |
Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering
This work is licensed under a Creative Commons Attribution 4.0 International License.