Abstract
Because there is no temporal information available, rain removal with a single image is more challenging than that with a video. In this paper, we present a weighted median guided filtering method for rain removal with a single image. It consists of two filtering operations. Firstly, a weighted median filter is convoluted with an input rainy image to obtain a coarse rain-free image; then, guided filter is employed to obtain a refined rain-free image, where the coarse rain-free image is used as a guided image and convoluted with the input rainy image via guided filter. Experimental results show that the proposed method generated comparable results to the state-of-the-art algorithms with low computation cost.
Highlights
In rainy days, the performance of outdoor vision systems will significantly degrade due to visibility obstruction, deformation, and blurring caused by raindrops
Based on what was mentioned above, in an attempt to preserve more complex structures in the rain-removed images, in this paper, we present a weighted median guided filtering method for rain removal with a single image
For quantitative evaluation of different methods on synthetic rainy images, because the ground-truth images are available, we employ the indexes of peak signal-to-noise ratio (PSNR) [12] and Structure Similarity Index (SSIM) [13] on the luminance channel as evaluation measures
Summary
The performance of outdoor vision systems will significantly degrade due to visibility obstruction, deformation, and blurring caused by raindrops. The main idea of this kind of methods is to explore the redundant temporal information from multiple images Though such kind of method works well, it heavily depends on the temporal contents in videos and cannot be applied for the case where only a single image is available. Based on what was mentioned above, in an attempt to preserve more complex structures in the rain-removed images, in this paper, we present a weighted median guided filtering method for rain removal with a single image.
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