Analysis of the Multi-Dimensional Scale Saliency Algorithm and Its Application to Texture Categorization

•A new approach for multi-dimensional Scale Saliency (MDSS) was lately introduced [1] • The MDSS algorithm is based on alternative entropy and divergence estimation methods whose complexity does not exponentially increase with data dimensionality • In this paper: –We apply the MDSS algorithm to the texture categorization problem –We provide further experiments in order to assess the suitability of different estimators –We propose a new divergence measure based on the k-d partition algorithm