Coherency estimation based on spectrum Gaussian-Hermite moments

摘要

The process of identifying regions with similar texture and separating regions with different texture is an essential step towards identifying surfaces and objects in the image. This paper describes a method of processing discontinuities of the gray level image. Moments are widely used in image analysis and pattern recognition. The Gaussian-Hermite moments, as one kind of orthogonal moments, are proposed to estimate coherency of the image in this paper. The local image is firstly converted into frequency domain from spatial domain, and then coherency is measured by matrix constructed of Gaussian-Hermite moments of energy within frequency domain. Compared to other methods, such as coherency estimation based on geometric moments, cross correlation, eigenstructure, semblance, or gradient vector field, the experimental results show a good performance in feature representation, regions recognition and regions.