- Title
- Deep Learning Approach to Image Deblurring and Image Super-Resolution using DeblurGAN and SRGAN
- Creator
- Kuhlane, Luxolo L
- Creator
- Brown, Dane L
- Creator
- Connan, James
- Creator
- Boby, Alden
- Creator
- Marais, Marc
- Subject
- To be catalogued
- Date Issued
- 2022
- Date
- 2022
- Type
- text
- Type
- article
- Identifier
- http://hdl.handle.net/10962/465157
- Identifier
- vital:76578
- Identifier
- xlink:href="https://www.researchgate.net/profile/Luxolo-Kuhlane/publication/363257796_Deep_Learning_Approach_to_Image_Deblurring_and_Image_Super-Resolution_using_DeblurGAN_and_SRGAN/links/6313b5a01ddd44702131b3df/Deep-Learning-Approach-to-Image-Deblurring-and-Image-Super-Resolution-using-DeblurGAN-and-SRGAN.pdf"
- Description
- Deblurring is the task of restoring a blurred image to a sharp one, retrieving the information lost due to the blur of an image. Image deblurring and super-resolution, as representative image restoration problems, have been studied for a decade. Due to their wide range of applications, numerous techniques have been proposed to tackle these problems, inspiring innovations for better performance. Deep learning has become a robust framework for many image processing tasks, including restoration. In particular, generative adversarial networks (GANs), proposed by [1], have demonstrated remarkable performances in generating plausible images. However, training GANs for image restoration is a non-trivial task. This research investigates optimization schemes for GANs that improve image quality by providing meaningful training objective functions. In this paper we use a DeblurGAN and Super-Resolution Generative Adversarial Network (SRGAN) on the chosen dataset.
- Format
- computer
- Format
- online resource
- Format
- application/pdf
- Format
- 1 online resource (6 pages)
- Format
- Publisher
- Southern Africa Telecommunication Networks and Applications Conference (SA TNAC)
- Language
- English
- Relation
- Kuhlane, L.L., Brown, D., Connan, J., Boby, A. and Marais, M., Deep Learning Approach to Image Deblurring and Image Super-Resolution using DeblurGAN and SRGAN
- Relation
- 2022
- Rights
- Publisher
- Rights
- Use of this resource is governed by the terms and conditions of Southern Africa Telecommunication Networks and Applications Conference (SA TNAC) Statement (https://www.satnac.org.za/)
- Rights
- Closed Access
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