Multi‐stage filtering for single rainy image enhancement
Zhenghao Shi, Yaowei Li, Minghua Zhao, Yaning Feng, Lifeng He · IET Image Processing · 2018
Rain image enhancement is important for outdoor computer vision applications. In this study, the authors propose a multi‐stage filtering method for single rainy image enhancement. It is based on their new rainy image model, and consists of two main operations: rain streaks removal and rain fog removal. For rain streaks removal, based on one key observation that the low‐pass version of a rainy image and that of a non‐rainy image of the same scene are almost the same after appropriate low‐pass filtering, they remove rain streaks from rainy images by decomposing an input rainy image (or a rainy component image) into the low‐frequency (LF) part and the high‐frequency (HF) part via an LF smooth filter, i.e. the traditional Gaussian filter with a simple subtraction operation in multiple different stages. After rain streaks removal, dark channel prior‐based method was employed for rain fog removal. Experimental results show that the proposed algorithm generated comparable outputs with most of the state‐of‐the‐art algorithms with low computation cost.