Research on removal algorithm of rain and snow from images based on improved snake model
基于改进snake模型的图像中雨雪去除算法研究*

As for the adverse effects of rain and snow on image processing, this paper proposed a new removal algorithm for rain and snow based on improved snake model. Normally, conventional snake model determined the initial contour points by hand, which only applied to clear target edge. Aiming at the non-obvious outline of rain and snow, this algorithm could automatically obtain the initial sequential contour points using fuzzy connectedness. Moreover, using conventional snake model, blurred edge induced by high-speed drop of rain or snow cause that the initial contour points could not accurately converge to the boundary points. Therefore, the algorithm utilized fuzzy similarity function to construct the external energy function of snake model in order to locate the boundary of rain and snow precisely, and then smoothed and fitted the profile of rain and snow through cubic B-spline. In addition, applied the H component of the HSI color space to reduce the impact of moving objects on rain and snow removal. A lot of experiments were processed. And the results show that the proposed algorithm is more suitable to identify rain or snow with different velocities, and better to eliminate the impact of moving objects.