Abstract：The traditional background modeling method based on Gaussian model and the simple background subtraction method are difficult to accurately distinguish vehicles and shadows. Therefore， a vehicle moving shadow removal approach based on zero-tree wavelet (ZW) for traffic video is proposed in this paper. Firstly, the motion foreground image containing noise is converted to HSV color space and then the S channel and the V channel are processed with multilevel down-sampling wavelet transform. Secondly, by constructing the ZW mask of the motion foreground， the coefficients in different scale subbands are associated, and the mask values of fine scale subband can be guided and corrected by the father sub-band coefficients. Consequently, the accuracy of adaptive threshold of the subband is improved. By combining the shadow color characteristics， the distinction degree of judging vehicles and shadows is improved. A large number of simulation experiments verify the effectiveness of the proposed approach.
王相海，王凯，刘美瑶，苏元贺，宋传鸣. 基于零树小波的交通视频车辆运动阴影滤除方法[J]. 模式识别与人工智能, 2016, 29(12): 1104-113.
WANG Xianghai, WANG Kai, LIU Meiyao, SU Yuanhe, SONG Chuanming. Vehicle Moving Shadow Removal Approach Based on Zero-Tree Wavelet for Traffic Video. , 2016, 29(12): 1104-113.
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