Single image rain removal based on part-based model
Chia‐Hung Yeh, Pin-Hsian Liu, Cheng-En Yu, Chih‐Yang Lin · 2015
There are many outdoor vision applications such as surveillance and navigation. One of the challenges is rain removal, especially the rain removal from a single image. In this paper, a single rain image is divided into the high frequency part and the low frequency part by the Gaussian filter. Non-negative matrix factorization (NMF) is used to remove the rain streaks in the low frequency part. Then, Canny edge detection is applied to deal with the rain in the high frequency and the block copy method is employed to preserve the image quality. After that, we applied a rain dictionary to further divide the high frequency into rain and non-rain parts. The experimental results show that the proposed method is better than the state-of-the-art methods, especially in the high frequency part.