The Research On Rain And Snow Removal In Image Sequences

Airport runway debris seriously influenced the safety of aircraft flight. Rain and snow had very adverse effects on airport runways debris detection system based on visual. By eliminating the impact of rain and snow, the accuracy of airport runways debris detection system and the support ability and efficiency of our airports safe operation were impoved. So this paper proposed new removal algorithms with the shape characteristics and the distribution characteristics of rain and snow. The result of this paper mainly includes:First, this paper proposed a new removal algorithm for rain and snow based on fuzzy connectedness. According to the impact of rain and snow on the pixel brightness, multiple seed points would be identified for fuzzy growth, and relative fuzzy connectedness was used to updated the seed which the pixels to be determined belonged to, through adding distance factor, the termination of the growth conditions of fuzzy was improved; In order to reduce the impact of moving objects on rain and snow removal, the H element of the HSI color space was applied to distinguish moving objects. Experimental examples show that the proposed algorithm was more suitable to identify different velocity of rain or snow for different levels of rain and snow, and better to eliminate the impact of moving objects than the traditional methods.Secondly, 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 determines the initial contour points by hand, which only applies 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, the H component of the HSI color space was applied 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 was more suitable to identify rain or snow with different velocities, and better to eliminate the impact of moving objects.