Unsupervised classification of remotely sensed images via independent component analysis

In this paper, some independent component analysis based unsupervised classification methods for remotely sensed imagery are proposed. In order to determine the validity of the proposed unsupervised classification methodology, some clustering quality metrics are used. According to the obtained results, the successes of proposed methods are compared.