Publication Type : Journal Article
Publisher : Rajagiri School of Social Sciences, Kalamassery, Kochi
Source : International Journal of Applied Engineering Research, International Journal of Applied Engineering and Research ( IJAER), Volume 10, Issue 73, Department of Computer Science, Rajagiri School of Social Sciences, Kalamassery, Kochi (2015)
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking
Department : Electronics and Communication
Year : 2015
Abstract : Considering the fact that involving spatial information in feature extraction significantly improves the classification accuracies, this paper focuses on Variational Mode Decomposition (VMD) and Empirical Mode Decomposition (EMD) as the featureextraction algorithms. Both the algorithms decompose an input image into different modes with each mode including different regions of frequency with unique properties. Here, the proposed method includes processing the same set of data with two different decomposition methods to compare the effect of the methods on the standard dataset. The method incorporates a preprocessing technique for noisy band removal, processing technique for feature extraction, band selection methods for dimensionality reduction and classification technique for result validation
Cite this Research Publication : N. Nechikkat, Sowmya, and Dr. Soman K. P., “A Comparative Analysis of Variational Mode and Empirical Mode Features on Hyperspectral Image Classification”, International Journal of Applied Engineering Research, vol. 10, no. 73, 2015.