SAR-image classification with a directional-oriented discrete Hermite transform and Markov random fields

A novel classification scheme for SAR images based on the perceptual classification of image patterns in the discrete Hermite transform (DHT) domain over a roughly hexagonal sampling lattice has been developed. In order to obtain the DHT referred to a rotated coordinate system the set of coefficients of a given order are mapped through a unitary transformation based on the generalized binomial function. This representation allows a perceptual classification, including constant patterns (0-D), oriented structures (1-D), and non-oriented structures (2-D). Classification is based on light adaptation and contrast masking properties of the human vision. Finally, classification is improved by means of a probabilistic approach based on Markov random fields.