In order to realize the automatic optimization of the optimal parameters of grayscale image enhancement, an adaptive image enhancement method based on an improved squirrel search algorithm is proposed. A bilateral search strategy is introduced into the position updating of the squirrels on normal trees to increase the likelihood of obtaining an optimal solution. A cyclone foraging strategy is used to update the position of the squirrels on acorn trees to improve the convergence rate and search accuracy of the algorithm. In addition, the proposed squirrel search algorithm with bilateral search and cyclone foraging (BCSSA) is compared with the bat algorithm (BA), whale optimization algorithm (WOA), basic squirrel search algorithm (SSA), and two improved SSAs on CEC 2017 test suite. The results indicate that BCSSA has higher stability and faster convergence rate. Finally, the proposed BCSSA is applied to grayscale image enhancement, and its performance is compared with that of the classical histogram equalization method and SSA in terms of four evaluation indicators, which thus validates the superiority of BCSSA.