Aiming at the problem that the traditional computer cannot meet the expectation in the information analysis and post- processing of complex images, a new photoelectric image enhancement strategy was proposed, which used the improved original firefly algorithm ( FA) to dynamically optimize and adjust the gray curve on the incomplete Beta function. The new strategy mainly improved the traditional FA algorithm from the perspective of the algorithm, introduced a new attraction formula for the original attraction degree that was prone to local optimality, added self-perturbation to solve the problem that the algorithm fell into local oscillation, and avoided the iterative detection link that fell into local optimality. The improved new Firefly Algorithm Growth ( FAG) was combined with an incomplete Beta function to dynamically search for image gray curve under optimal value. The improved FAG was compared with the old and new FA algorithms on four common benchmark functions to test their performance, and the results showed that the improved FAG algorithm was superior in terms of performance. In experiments where the same image was enhanced by the improved FAG combined with incomplete Beta and FA combined with incomplete Beta, the histogram algorithm was added to enhance the image as the control group, and the comprehensive results showed that the improved new strategy was superior. The results show that the swarm intelligence algorithm has a good application value in the combination of image processing means to achieve the purpose of image enhancement. The new strategy can effectively enhance photoelectric images under the condition of low contrast.