Generative Adversarial Networks based method for Generating Photo-Realistic Super Resolution Images

Since the word picture was coined, resolution has always been a challenge. Many studies have been conducted to generate high-resolution photographs, but none have been able to develop a process that is both time and quality effective. As a result, the super resolution issue is discussed in this paper using single-processing techniques. Deep learning methods are used to solve the same problem. The method suggested here will transform a low-resolution image into a high-resolution image of a pleasant and satisfactory quality. This can be accomplished using GANs (Generative Adversarial Networks) with significant up scaling factors.