In this work, we present a method based on spectral clustering algorithm for hyperspectral urban image unsupervised classification, which tries to overcome the following two issues of the kmeans ...

A new algorithm for spectral clustering is depicted. This algorithm can cluster a large number of samples (in the order of 50000 samples) that would be impossible to cluster with current approaches.