Single Image Super Resolution using Deep Learning: A Survey
| Author(s) | : | Yogeshvari Makwana, Prashant B.swadas, Pranay S. patel |
| Institution | : | Department of Computer, BVM Engineering College |
| Published In | : | Vol. 7, Issue 4 — April 2020 |
| Page No. | : | 22-27 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
Single image super-resolution, which is used to restore high-resolution image from a single lowresolution image, is a difficult challenging problem in computer field. In recent times, dominant deep learningalgorithms have been applied to Single image super resolution and have shown an highly efficient performance. In thispaper, we surveyed deep learning-based super resolution method known as a super resolution convolutional neuralnetwork (SRCNN) that takes the low-resolution image as the input and outputs the high-resolution one. SRCNN has anon-complex structure yet provides high quality and fast speed. We get quick results for practical online usage. Hence,survey is carried out on different networks like Generative Adversarial Networks (GAN) and Convolutional NeuralNetwork comparison between quality and speed.
Yogeshvari Makwana, Prashant B.swadas, Pranay S. patel, “Single Image Super Resolution using Deep Learning: A Survey”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 7, Issue 4, pp. 22-27, April 2020.
