An unsupervised change detection method based on fast expectation-maximization (EM) algorithm and fuzzy fusion for multi-band remote sensing images was proposed. First, fast EM iteration algorithm based on histogram of image difference in each band was used to obtain the change class threshold and change information. Second, the fuzzy theory and relationship matrix were adopted to integrate the classification information of all bands, and the final changed and un-changed map of the bitemporal remote sensing images were obtained. Thus, the change detection image was formed. The real bitemporal SPOT5 and Landsat TM satellite imagery were performed to evaluate the effectiveness of the proposed method. The results show that the proposed method reduces the processing time and gets better detection effectiveness comparing with other methods.