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Journal of Sensors
Volume 2017, Article ID 9702612, 14 pages
https://doi.org/10.1155/2017/9702612
Research Article

An Unsupervised Algorithm for Change Detection in Hyperspectral Remote Sensing Data Using Synthetically Fused Images and Derivative Spectral Profiles

1School of Convergence & Fusion System Engineering, Kyungpook National University, Sangju 37224, Republic of Korea
2School of Engineering and Computing Sciences, Texas A&M University-Corpus Christi, 6300 Ocean Dr., Corpus Christi, TX 78412, USA
3School of Civil Engineering, Chungbuk National University, 1, Chungdae-ro, Seowon-gu, Cheongju, Chungbuk 28644, Republic of Korea

Correspondence should be addressed to Jaewan Choi; rk.ca.kubgnuhc@iohcnaweaj

Received 25 April 2017; Accepted 9 July 2017; Published 10 August 2017

Academic Editor: Hyung-Sup Jung

Copyright © 2017 Youkyung Han et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Youkyung Han, Anjin Chang, Seokkeun Choi, Honglyun Park, and Jaewan Choi, “An Unsupervised Algorithm for Change Detection in Hyperspectral Remote Sensing Data Using Synthetically Fused Images and Derivative Spectral Profiles,” Journal of Sensors, vol. 2017, Article ID 9702612, 14 pages, 2017. https://doi.org/10.1155/2017/9702612.