Siberian Federal University 
- Issue
- Journal of Siberian Federal University. Engineering & Technologies. 2017 10 (6)
- Authors
- Melnikov, Pavel V.; Pestunov, Igor A.; Rylov, S.A.
- Contact information
- Melnikov, Pavel V.: Institute of Computational Technologies SB RAS 6 Akademika Lavrentieva, Novosibirsk, 630090, Russia; ; Pestunov, Igor A.: Institute of Computational Technologies SB RAS 6 Akademika Lavrentieva, Novosibirsk, 630090, Russia; ; Rylov, S.A.: Institute of Computational Technologies SB RAS 6 Akademika Lavrentieva, Novosibirsk, 630090, Russia
- Keywords
- hyperspectral images; local context; spectral-spatial classification
- Abstract
This paper reviews three methods of spectral-spatial classification for hyperspectral images of high spatial resolution: 1) pixelwise classification with post-filtering of resulting class map; 2) spectralspatial classification based on geometric moments; 3) spectral-spatial classification based on segmentation. The paper provides the results of experimental comparison of these methods. The experiments are based on classification of images obtained by airborne hyperspectral sensor
- Pages
- 805-811
- Paper at repository of SibFU
- https://elib.sfu-kras.ru/handle/2311/35014
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).