Publication Type:

Journal Article

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)

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 V., and 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.

207
PROGRAMS
OFFERED
5
AMRITA
CAMPUSES
15
CONSTITUENT
SCHOOLS
A
GRADE BY
NAAC, MHRD
8th
RANK(INDIA):
NIRF 2018
150+
INTERNATIONAL
PARTNERS