For image deblurring application with defocus blurring effect, a parameter estimation method based on Grayscale Mean Gradient (GMG) and Particle Swarm Optimization (PSO) algorithm was proposed to estimate the blurring parameter. First, a group of point spread functions with different blurring radius were randomly generated by PSO algorithm to process a blurred image with Wiener filtering algorithm, then a series of restored images were obtained and the corresponding GMG values were calculated. Secondly, concerning the property that the definition of an image is positively varied with its GMG value, which is shown by experimental results, the GMG values were taken as the fitness function values of the PSO algorithm, then a particle with maximum fitness was found, and the corresponding blurring parameter was taken as the final result of estimation. The experimental results show that the proposed algorithm outperforms spectral estimation method and cepstrum estimation method in estimation accuracy, especially in the case with large blur radius.