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Single-image-based rain streak removal using multidimensional variational mode decomposition and bilateral filter

机译:基于多维变分分解和双边滤波器的单图像雨条去除

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摘要

The removal of rain streaks is critical for cameras in rainy weather conditions. Traditional single-image-based methods suffer from the defects of losing detail information and being time consuming. This study presents a single-image-based rain streak removal using multidimensional variational mode decomposition (MVMD). Rainy image is decomposed using MVMD into several subimages with specific directional and frequency characteristics. Thus, the rain streak components will be limited to one or two subimages, which are called rainy subimages. Rainy subimages are determined based on the directional characteristics. The subimages are narrow band-limited. Therefore, the rainy subimages contain few outline and detail information with other frequency and directional characteristics. Thus, the derain procedure that is performed on the rainy subimages will preserve most of the detailed information. The rain components are removed from the rainy subimages by a bilateral filter. The rain components can be successfully removed from the rainy image through the summation of the subimages without rain components and the filtered rainy subimages. The experimental results show that the proposed method has good rain removal capability while retaining most of the details with a lower running time compared with other existing methods. (C) 2017 SPIE and IS&T
机译:对于阴雨天气条​​件下的相机来说,去除雨水条纹至关重要。传统的基于单图像的方法具有丢失细节信息和耗时的缺点。这项研究提出了使用多维变分模式分解(MVMD)的基于单个图像的雨斑去除。使用MVMD将多雨图像分解为具有特定方向和频率特性的几个子图像。因此,降雨条纹分量将被限制为一个或两个子图像,这被称为降雨子图像。根据方向特性确定多雨的子图像。子图像是窄带限制的。因此,多雨的子图像包含很少的轮廓和细节信息以及其他频率和方向特征。因此,在多雨子图像上执行的去黑头程序将保留大多数详细信息。雨水分量通过双边过滤器从雨水子图像中删除。通过将没有降雨分量的子图像和经过过滤的降雨子图像相加,可以成功地从降雨图像中删除降雨分量。实验结果表明,与其他现有方法相比,该方法具有良好的除雨能力,同时保留了大部分细节,并且运行时间较短。 (C)2017 SPIE和IS&T

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