Single frame infrared image super-resolution algorithm based on generative adversarial nets

Image processing makes super-resolution infrared image reconstruction effectively improve infrared images resolution, which breaks through hardware performance limits. Based on deep learning, super-resolution method is applied to infrared image, which 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 network can improve magnification, which can access to better high-frequency details of the restoration and can sharpen image edge and avoid blurred super-resolution infrared images.