Blurred image restoration is an important task in the field of computer vision and image processing. In view of the problem of score function has relatively small differences and weak optimization function of mind evolutionary algorithm (MEA) in image restoration based on combination of MEA and wavelet neural network (WNN), an improved MEA-WNN image restoration model is proposed. The difference between score function is increased by using power law transformation and logistic regression function, therefore, the selecting function of MEA is enhanced significantly. Comparative experiments are conducted between improved and traditional WNN and MEA-WNN-based image restoration model, the improved model can increase the peak signal-to-noise ratio (PSNR) by 15% and 6.5%, and structural similarity (SSIM) by 6.1% and 5% respectively. Effectiveness and superiority of improved model is proved by some experimental results.