The invention provides a super-resolution deblurring method of a generated antagonistic network, which comprises the following steps: S1, utilizing a DRCN network structure to form a super-resolutiondepth convolution network, and establishing an antagonistic network model; S2, combining the SRGAN network cost function to improve the countermeasure network performance; S3, selecting clear picture,adding Gaussian noise and motion blur to realize training. The present invention analyzes the characteristics of motion blur, Designing the artificial noise of samples, adding defocus fuzzy kernel and multi-direction motion fuzzy kernel, realizing the super-resolution deblurring of the blurred image with double magnification, and analyzing the blurred image taken by UAV, can greatly reduce the influence of professional knowledge and experience on the design of deblurring algorithm.