Remotely Sensed Image Classification Using Sparse Representations of Morphological Attribute Profiles

Abstract

In recent years, sparse representations have been widely studied in the context of remote sensing image analysis. In this paper, we propose to exploit sparse representations of morphological attribute profiles for remotely sensed image classification. Specifically, we use extended multiattribute profiles (EMAPs) to integrate the spatial and spectral… (More)
DOI: 10.1109/TGRS.2013.2286953

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@article{Song2014RemotelySI, title={Remotely Sensed Image Classification Using Sparse Representations of Morphological Attribute Profiles}, author={Benqin Song and Jun Li and Mauro Dalla Mura and Peijun Li and Antonio J. Plaza and Jos{\'e} M. Bioucas-Dias and Jon Atli Benediktsson and Jocelyn Chanussot}, journal={IEEE Transactions on Geoscience and Remote Sensing}, year={2014}, volume={52}, pages={5122-5136} }