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An Unsupervised Spectral Matching Classifier Based on Artificial DNA Computing for Hyperspectral Remote Sensing Imagery
2014
IEEE Transactions on Geoscience and Remote Sensing
Hyperspectral remote sensing image clustering, with the large volume, high dimensions, and temporal-spatial spectral diversity, is a challenging task due to finding interesting clusters in the sparse feature space. In this paper, a novel hyperspectral clustering algorithm, namely, an unsupervised spectral matching classifier based on artificial DNA computing (UADSM), is proposed to perform the task of clustering different ground objects in specific spectral DNA feature encoding subspaces. UADSM
doi:10.1109/tgrs.2013.2282356
fatcat:7owvypz5qrfwvdk4aphkkvprkq