2023/05/03 by Chaobing Zheng, Zheng, Chaobing, Jun Jiang +5
Computer Science · Engineering · #Advanced Image Fusion Techniques #Advanced Image Processing Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #Image Enhancement Techniques #Image and Video Processing (eess.IV) #Machine vision and scene understanding #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2305.02100
openalex publication_date 2023/05/03 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
It is challenging to remove rain-steaks from a single rainy image because the rain steaks are spatially varying in the rainy image. Although the CNN based methods have reported promising performance recently, there are still some defects, such as data dependency and insufficient interpretation. A single image deraining algorithm based on the combination of data-driven and model-based approaches is proposed. Firstly, an improved weighted guided image filter (iWGIF) is used to extract high-frequency information and learn the rain steaks to avoid interference from other information through the input image. Then, transfering the input image and rain steaks from the image domain to the feature domain adaptively to learn useful features for high-quality image deraining. Finally, networks with attention mechanisms is used to restore high-quality images from the latent features. Experiments show that the proposed algorithm significantly outperforms state-of-the-art methods in terms of both qualitative and quantitative measures.