Snow fluff detection and removal from video images
Tangwen Yang, Venant Nsabimana, Bufang Wang, Yantao Sun, Xiaoqing Cheng, Honghui Dong, Yong Qin, Bin Zhang, Felix Ingrabire · IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society · 2017
Snow detection and removal from video images is very challenging. Normally the snowflakes affect only on a very small region of an image, hence the confusion to determine which region should be considered and which one should not. In this paper, a frame difference method with five successive frames is first presented to detect the snow pixels from image background, but the method didn't work well in the case of heavy snow. Then a new technique has been implemented which uses the L0gradient minimization approach to remove the snow pixels. This technique can control how many non-zero gradients are resulted in the image, and is independent of local features, but instead locates important edges globally. These salient edges are preserved and the low amplitude and insignificant details are diminished. The snow pixels are then removed in this way. Experimental results show that this method is a highly efficient algorithm even under heavy snow conditions, while preserving the details of the image.