针对图像分割中小波域多尺度马尔可夫模型(MRMRF-W)无法有效描述图像非线性特征，提出了一种在形态小波域下的多尺度MRF模型（MRMRF-MW）,实现纹理图像分割。该模型结合了形态小波和MRF各自的优势，能够对图像进行非线性多尺度分解，并在各尺度上进行空间关系建模。通过对两个纹理图像库（Brodatz纹理库、Prague纹理库）中图像的分割实验，验证了该模型的有效性。

Because of the disadvantages of Multi-resolution Markov random field in wave domain for the description of the nonlinear features of the image, this paper proposes a new Multi-resolution Markov random model in morphological wavelets domain to partition the texture images. Morphological wavelets can do a nonlinear multi-resolution decomposition of images. Markov random field can model the spatial relationship of pixels in each resolution. The multi-resolution Markov random model in morphological wavelets domain combines the benefits of morphological wavelets and Markov random field. The experiments of texture images segmentation validate of our model, where the test texture images are employed from the Brodatz and Prague texture image databases.