Year: 2022
Type: preprint
Abstract: Image super-resolution is an important research area in computer vision that has a wide variety of applications including surveillance, medical imaging etc. Real-world signal image super-resolution has become very popular now-a-days due to its real-time application. There are still a lot of scopes to improve real-world single image super-resolution specially during challenging weather scenarios. In this paper, we have proposed a new algorithm to perform real-world single image super-resolution during rainy condition. Our proposed method can mitigate the influence of rainy conditions during image super-resolution. Our experiment results show that our proposed algorithm can perform image super-resolution decreasing the negative effects of the rain.
Source: arXiv (Cornell University)
Author: Uddin, Mohammad Shahab
Institution: Old Dominion University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4283077191