POWER SPECTRAL CLUSTERING ON HYPERSPECTRAL DATA

Abstract : Classification of remotely sensed data is an important task for many practical applications. However, it is not always possible to get the ground truth for supervised learning methods. Thus unsupervised methods form a valuable tool in such situations. Such methods are referred to as clustering methods. There exists several strategies for clustering the given data-K-means, density based methods, spectral clustering etc. Recently we proposed a novel method for clustering data-Power Spectral Clustering. In this article we aim to introduce the method in the context of Geoscience and Remote Sensing, apply the method to hyperspectral data and validate its applicability to remotely sensed images.
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https://hal.archives-ouvertes.fr/hal-01484896
Contributeur : Aditya Challa <>
Soumis le : mercredi 8 mars 2017 - 05:30:36
Dernière modification le : dimanche 12 mars 2017 - 01:06:17

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PowerSpectral_IGARSS2017.pdf
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  • HAL Id : hal-01484896, version 1

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Aditya Challa, Sravan Danda, B S Daya Sagar, Laurent Najman. POWER SPECTRAL CLUSTERING ON HYPERSPECTRAL DATA. 2017. <hal-01484896>

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