Multi‐stage filtering for single rainy image enhancement

Abstract

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.