A gray image enhancement method is proposed based on an improved bacterial foraging optimization algorithm, so that the problems of the insufficient detail processed by the traditional image enhancement technology and the offset of histogram distribution after the transformation are solved. To avoid becoming prone to fall into the defects of premature convergence and other poor performances in swarm intelligence algorithms when optimizing high dimensional functions, a gray-scale image enhancement problem whose dimensions are high and variational is converted into a fixed two-dimensional parameters optimization problem of the incomplete Beta function. Simulation results show the effectiveness of the proposed method. Comparing with other methods, enhanced image makes the details more natural, the histogram distribution more uniform, and the light and dark areas more reasonable.