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Satellite Image Classification using Neural Network

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IJCA Proceedings on International Conference on Quality Up-gradation in Engineering Science and Technology
© 2017 by IJCA Journal
ICQUEST 2016 - Number 3
Year of Publication: 2017
Authors:
Pranjali Dahikar
Yogita Dubey

Pranjali Dahikar and Yogita Dubey. Article: Satellite Image Classification using Neural Network. IJCA Proceedings on International Conference on Quality Up-gradation in Engineering Science and Technology ICQUEST 2016(3):1-4, August 2017. Full text available. BibTeX

@article{key:article,
	author = {Pranjali Dahikar and Yogita Dubey},
	title = {Article: Satellite Image Classification using Neural Network},
	journal = {IJCA Proceedings on International Conference on Quality Up-gradation in Engineering Science and Technology},
	year = {2017},
	volume = {ICQUEST 2016},
	number = {3},
	pages = {1-4},
	month = {August},
	note = {Full text available}
}

Abstract

The data from remote sensing have been used from so many years for image classification and its development algorithm, which can be applied to several different fields like forestry, educational purpose, management etc. In this paper, a classification method of a high resolution satellite image using neural network is proposed. First noisy bands were removed using dimensionality reduction technique. Minimum noise fraction (MNF) reduces the spatial dimension of hyperspectral image (HSI). Then, learning vector quantization (LVQ) based algorithm and some samples from groundtruth map are used to train the network for image classification and finally, accuracy is estimated. The main goal of this paper is to determine the ability of artificial neural network system for classifying satellite image by algorithm based on LVQ.

References

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