| Issue |
E3S Web Conf.
Volume 75, 2019
Regional Problems of Earth Remote Sensing (RPERS 2018)
|
|
|---|---|---|
| Article Number | 01010 | |
| Number of page(s) | 5 | |
| Section | Methods and Algorithms for Image Processing | |
| DOI | https://doi.org/10.1051/e3sconf/20197501010 | |
| Published online | 14 January 2019 | |
Extension of training set using mean shift procedure for aerospace images classification
Institute of Computational Technologies of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
* Corresponding author: yorikmail@gmail.com
An effective method of training set extension for aerospace images classification is proposed. The method is based on mean shift procedure with respect to spatial information. It allows considering the unlabeled data structure. The results of experimental study using the Salinas hyperspectral image are presented, proving the effectiveness of the proposed method.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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