An adaptive model for texture analysis

This paper proposed a new adaptive texture model applicable to a wide variety of texture types. In this model, the texture field is assumed to be a realization of a regular homogeneous random field and can be decomposed into two components which are indeterministic and deterministic components as in the Wold (1954) texture model. These two components are represented by Gaussian Markov random field (GMRF) model and multichannel filtering model based on the Gabor function (Gabor model), respectively. According to the different ratio of composition from each component in the texture model, an adaptive factor was proposed in the new model. The results of a classification experiment on 81 Brodatz texture images are presented which demonstrated that the new model can better represent a wide variety of textures