Entropy Estimation and Multi-Dimensional Scale Saliency

In this paper we survey two multi-dimensional Scale Saliency approaches based on graphs and the k-d partition algorithm. In the latter case we introduce a new divergence metric and we show experimentally its suitability. We also show an application of multi-dimensional Scale Saliency to texture discrimination. We demonstrate that the use of multi-dimensional data can improve the performance of texture retrieval based on feature extraction.