Real-World Single Image Super-Resolution Under Rainy Condition

TL;DR

This paper introduces a novel algorithm for real-world single image super-resolution that effectively reduces rain effects, improving image quality in rainy conditions for practical applications.

Contribution

The paper presents a new super-resolution method specifically designed to mitigate rain effects in images, addressing a challenging real-world scenario.

Findings

The proposed algorithm improves image clarity during rainy conditions.

Experimental results demonstrate reduced rain influence in super-resolved images.

The method outperforms existing approaches in rainy weather scenarios.

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.