Adaptive differential evolution fuzzy clustering algorithm with spatial information and kernel metric for remote sensing imagery

Abstract

In this paper, an adaptive differential evolution fuzzy clustering algorithm with spatial information and kernel metric for remote sensing imagery, namely KADESFC, is proposed. In KADESFC, the clustering problem is transformed into an optimization problem, which minimizes a proposed kernelized objective function with an adaptive spatial constraint term. Differential evolution algorithm is utilized to optimize the kernelized objective function, which uses several differential evolution operators. Experimental results on two remote sensing images show that the proposed algorithm is promising compared with several traditional clustering algorithms. © 2013 Springer-Verlag.