Multiscale estimation of vector field anisotropy application to texture characterization

摘要

This paper deals with the characterization of the anisotropy of textured images. It is well known that either the dominant direction or the texture anisotropy strongly depends on the scale used for the observation. In this paper we propose a new operator for the estimation of the dominant direction, the directional mean vector (DMV), which can be computed at any observation scale. Then, we present a new indicator for the estimation of the DMV field anisotropy. This indicator, called I_(so), is computed at a given observation scale. I_(so) is based on the computation of the DMV field local differences. It is shown that the evolution of I_(so) versus the observation scale gives a curve which simultaneously characterizes the anisotropy of the texture and the size of the textural patterns. In order to establish this property, we build a specific texture model which allows to assess an analytical expression for I_(so). Finally, I_(so) is applied to the characterization of various images including synthetic textures, Brodatz textures and composite material images.