Real-World Single Image Super-Resolution Under Rainy Condition
This addresses image quality issues in surveillance and medical imaging under rainy weather, but appears incremental as it focuses on a specific weather scenario without broad SOTA claims.
The paper tackles real-world single image super-resolution in rainy conditions by proposing a new algorithm that mitigates rain influence, with results showing it decreases negative effects during super-resolution.
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.