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The multiresolution technique is one of the most important techniques for image segmentation. Wavelet transformation is a pixel-based method and is widely used for multiresolution segmentation approaches, but it suffers the deficiency of modeling the macrotexture pattern of a given image. In order to overcome such a problem, this letter extends the multiresolution technique from the pixel level to the region level and proposes a new image segmentation model by incorporating the multiregion-resolution and the Markov random field model. Experiments are conducted using synthetic-aperture-radar data and remote sensing images, which demonstrates that our method can improve the segmentation accuracy compared with the multiresolution method based on the pixel level.