Open Access Journal

ISSN : 2394 - 6849 (Online)

International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)

Monthly Journal for Electronics and Communication Engineering

Open Access Journal

International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)

Monthly Journal for Electronics and Communication Engineering

ISSN : 2394-6849 (Online)

PSO inspired Hyperspectral Image Classification

Author : Dr.K.Kavitha 1 Dr.S.Arivazhagan 2 W.Jenifa 3

Date of Publication :27th December 2017

Abstract: Hyperspectral Remote Sensing technology is used for identification and detection of objects on the earth. Hyperspectral images provide accurate classification than multispectral images but it suffers from over dimensionality problem. In order to overcome this drawback, Daubechies wavelet with Four taps (DB4) and Eight taps are used for extracting the features and to improve the classification performance Particle Swarm Optimization (PSO) technique is used for feature selection. Support Vector Machine (SVM) classifier is used for efficient classification. In this paper image acquired from AVIRIS sensor, Indian pines dataset is used. The overall accuracy obtained for DB4 and DB8 is 92% and 90% respectively

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