A Method for Removing Reflections from Water Surface Images Based on Pre-trained Image Restoration

Minghua Zhao, Rui Zhi, Shuangli Du, Jing Hu, Cheng Shi, Lin Wang

Abstract: Reflections on the water surface hinder the extraction of valuable information from water surface images. To remove reflections from water surface images, we construct a synthetic dataset and propose a multi-task network for water surface reflection detection and removal. Specifically, we first use a U-Net-based reflection detection module to generate a reflection mask, followed by a GAN-based network to remove the reflection. To extract multi-level features from the images, we design a color feature extraction network and a detail feature extraction network. Finally, to enhance the model's ability to remove large-area reflections, we pre-train the reflection removal network on an image restoration dataset. Experimental results on the proposed synthetic dataset and real water surface reflection images from the Internet show that our method significantly outperforms other methods in water surface reflection detection and removal.

External IDs:dblp:conf/icassp/ZhaoZDH0W25