A TENSOR DECOMPOSITION METHOD FOR UNSUPERVISED FEATURE LEARNING ON SATELLITE IMAGERY

We introduce a tensor factorization approach to unsupervised feature learning of hyper-spectral imagery, and demonstrate its effectiveness on land type classification of publicly available datasets. The results show that this approach can produce state of the art accuracy, compared to other methods for feature learning in the classification task.