Semi-supervised Learning with Graphs: Covariance Based Superpixels For Hyperspectral Image Classification

01/14/2019
by   Philip, et al.
0

In this paper, we present a graph-based semi-supervised framework for hyperspectral image classification. We first introduce a novel superpixel algorithm based on the spectral covariance matrix representation of pixels to provide a better representation of our data. We then construct a superpixel graph, based on carefully considered feature vectors, before performing classification. We demonstrate, through a set of experimental results using two benchmarking datasets, that our approach outperforms three state-of-the-art classification frameworks, especially when an extremely small amount of labelled data is used.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset