A Systematic Study of Super-Resolution Generative Adversarial Networks: Review

Visual representation of images has the edge of analyzing very deep down in many research areas so the problems can be understood very thoroughly. Images play a key role nowadays in several scientific and non-scientific fields such as medicine, geography, astronomy, gene sequencing, climate change, global warming, etc. But every time high-quality image is not available due to some constraints such as the quality of the camera, constraints of sending and receiving images, enforcing the camera to take the pic in microseconds in the area of radiology, nuclear reactor, during volcano eruption, etc. These are some of the prestigious sectors where HR quality of image always require. For solving these problems researchers have made out a very beautiful algorithm which is an SRGAN. This method become the center of various research for enhancing the resolution of the image. Every day many people do research and publish thousands of papers on this topic. This paper utilizes those studies and done the thorough review.