Image Super-Resolution using GAN - A study

Reconstructing low-resolution images to high-resolution images by building a neural network is quite challenging but can be used in many applications like medical imaging, public surveillance, or old photo recovery. Compared to previous methods, deep learning has a breakthrough in high-resolution accuracy and speed. By applying a deep network with Generative Adversarial Networks, this model aims to enhance low-resolution images to produce high-resolution images. The major focus is to reconstruct the image with high resolution by developing the image with low-resolution in order to preserve the main details in the reconstructed images.