We describe a novel technique for color image segmentation. This technique includes three components: a color space transformation, Markov random field expectation-maximization (MRF-EM) segmentation, and a multiresolution implementation termed ‘‘narrow band.’’ The color space transformation, from RGB to LUV, contributes to a perceptually reasonable segmentation result. The MRF-EM algorithm enables unsupervised segmentation and enforces a region smoothness constraint. The narrow-band, multiresolution implementation confines fine resolution processing to a small fraction of the image, thereby achieving acceleration over traditional multiresolution schemes. Experimental results with medical and TV images demonstrate the efficacy of the proposed technique.