In this work, we describe an approach to texture discrimination which builds statistical models based on the orthogonal wavelet representation of the image. These results compared with results from already known texture recognition methods seem encouraging. The method proposed in this paper has been tested in images of different structure. It is executed in two stages. In the first, a multiresolution approximation, up to a given resolution, is used for the decomposition of the image on a wavelet orthogonal basis. In the second stage, the set of the coefficients produced during the previous stage is modeled using a set of statistical measures. We used a set of four statistical measures that contribute to the most accurate texture description.
Stavros A. Karkanis,
"Statistical texture discrimination based on wavelet decomposition", Proc. SPIE 2762, Wavelet Applications III, (22 March 1996); doi: 10.1117/12.236008; https://doi.org/10.1117/12.236008