Super Resolution: A Simplified Approach Using GANs


Authors : Dr. Naveena C; Thanush M; Vinay N.B; Yaser Ahmed N

Volume/Issue : Volume 5 - 2020, Issue 7 - July

Google Scholar : http://bitly.ws/9nMw

Scribd : https://bit.ly/3jsA1iQ

DOI : 10.38124/IJISRT20JUL185

The project entitled “Super-Resolution: A simplified approach using GANs”, aims to construct a Higher Resolution image from a Lower Resolution image, without losing much detail. In other words, it is a process of up-sampling of an under-sampled image. In the current scenario, there is a high reliance on hardware improvements to capture better highresolution images. Although many digital cameras provide enough HR-imagery, the cost to construct and purchase such a high-end camera is high. Also, many computer vision applications like medical imaging, forensic and many more still have a strong demand for higher resolution imagery which is likely to be exceeded by the capabilities of these HR digital cameras we have today. To cope with this demand, a method to generate an HR image is shown using Generative Adversarial Networks (GANs).

Keywords : Super resolution, Deep learning, GANs, Image enhancement.

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