Entropodynamic Percentyle Filter

Abstract

Following work describes the implementation and experimental evaluation of the Entropodynamic Percentile Filter algorithm, allowing the detection of noise in images with many spectral components. The visual data block is processed to generate an edge map, independent of each spectral component, which makes possible the estimation of the information on the distribution of entropy in the spectrum. An appropriately constructed percentile filter separates noise carriers from highly informative layers. The quality of the method is verified with a series of experiments performed for the classification task.