Image coding with a directional-oriented Hermite transform on a hexagonal lattice
José Luis Silván-Cárdenas, Boris Escalante Ramírez · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2001
This paper presents a novel image compression scheme based on the perceptual classification of image patterns in the Discrete Hermite Transform (DHT) domain over a roughly hexagonal sampling lattice. The DHT analyzes a signal through a set of binomial filters which approximate the Gaussian derivatives with the advantage that they are computed efficiently. 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 that is locally specified. Such a transformation is based on the generalized binomial functions so that the rotation algorithm is efficient too. This representation allows a perceptual classification, which is achieved by thesholding the approximation errors that are obtained under the hypotheses that the underlying pattern is a constant (0-D), an oriented structure (1-D) or a non-oriented estructure (2-D). The threshold is based on light adaptation and contrast masking properties of the human vision. Then, a compression is obtained by elimination of coefficients that are visually irrelevant.