A searching method for an optimal code sequence of coded exposure is proposed based on the Memetic algorithm. The theoretical model for coded exposure imaging is analyzed and the criteria of fitness function for the optimal codeword selection is established. The Memetic algorithm framework is introduced to carry out the optimal code sequence search, and the genetic search algorithm is utilized to implement the global optimal solution search. On this basis, the simulated annealing algorithm is used to conduct the local optimal solution. The optimal codeword search results are obtained by the threshold constraint of the fitness function and the updated iteration of population and optimal solution. The research results show that, compared with other methods, the proposed algorithm can take into account both the global and the local optimal solutions, the obtained optimal code sequence has a better performance index, the execution efficiency is high, and the restored image has superior subjective and objective evaluation quality.