In this work, a literature review was performed to examine the different methods and applications used in super resolution image reconstruction. “Super-Resolution” (SR) is technique used for improving the images and videos resolution and so this approach has wide applications towards “Deep Learning” (DL) concepts. Through this article, detailed study is made on overview of recent applications of SR technique in DL. As a general rule, existing exploration on SR procedures can be separated into three classifications: supervised SR, unsupervised SR, and domain-specific SR. We additionally address other significant issues, for example, freely accessible benchmark informational collections and benchmarking measurements. Finally, we will conclude this survey by presenting the many possible ways in which the community may face in the future and open-ended questions.

image reconstruction, super resolution, image processing