Image processing makes super-resolution infrared image reconstruction effectively improve infrared images resolution, w hich breaks through hardw are performance limits. Based on deep learning, super-resolution method is applied to infrared image, w hich enables the super-resolution reconstruction of single-frame infrared image. Thus, better evaluation results are acquired. Derived from adversarial thoughts, adding a loss function based on discriminant netw ork can improve magnification, w hich can access to better high-frequency details of the restoration and can sharpen image edge and avoid blurred super-resolution infrared images.