In view of the threshold search difficulty in high-dimensional multilevel thresholding segmentation, a Biogeography-Based Optimization with Dynamic migration and salt & pepper mutation (BBOD) was proposed. Firstly, a dynamic migration operator was created, and it could add a dynamic disturbance factor to the feature values without migration occured in candidate solutions to increase the diversity of a population. Then,a new type of mutation operator was built to produce a salt and pepper disturbance for the feature values to be mutated,by which the local searching ability and convergence process of the algorithm were accelerated. Finally, the proposed BBOD algorithm was applied to the high-dimensional multilevel image thresholding segmentation based on minimum cross entropy. Experimental results show that BBOD is better in optimization performance and faster in operation speeds than standard BBO (Biogeography-Based Optimization)， BBOM(Biogeography-Based Optimization with Mutation),FFA(Firefly Algorithm)and CSA (Cuckoo Search Algorithm)，and its operation speed is 5 times as fast as that of FFA. The BBOD is fit to the threshold selection in the high-dimensional multilevel thresholding segmentation based on minimum cross entropy.