Multiresolution MRF-based texture segmentation using the Wreath Product Transform phase

We bring local phase and multiresolution analysis to the texture segmentation problem. A Markov random field characterization is still employed, except it is used to model phase correlations rather than intensity correlations. Since statistical characteristics of phase are typically quite different to those of intensity, there exists the potential for creating greater discrimination in its feature space. We apply the Wreath Product Transform and use the phase at higher scales to initiate the segmentation process. For textures defined by homogeneous regions of dominant local edges, we see that the new algorithm yields better segmentation than that obtained through conventional multiresolution algorithms based on lowpass data.