Cluster-space classification: a fast k-nearest neighbour classification for remote sensing hyperspectral data

Abstract

In this paper a fast k-nearest neighbour (k-NN) algorithm is presented which combines k-NN with a cluster-space data representation. Implementation of the algorithm is easier and classification time can be significantly reduced. Results from tests carried out with a Hyperion data set demonstrate that the simplification has little effect on classification performance and yet efficiency is greatly improved.