针对低对比度环境下拍摄目标图像所产生的低识别率问题，提出了一种基于小波提升算法的偏振信息融合方法，该方法采用偏振技术进行目标探测，应用小波提升算法所具有的计算量少、处理速度快等优点将偏振度和偏振角等信息分解为高频和低频部分，分别对高、低频系数采用不同规则进行融合，使得融合后目标边缘轮廓完全从低对比度环境中凸显出来，且细节信息完整、清晰，易于人眼对目标的识别。通过对大量低对比度场景下的目标进行识别及对融合结果进行评价，实验表明，该方法能有效地提高低对比度环境下目标的识别效率，验证了算法的可行性。

To resolve the low recognition ratio problem of the target captured in the low contrast environment, a polarization information fusion method based on wavelet lifting algorithm is proposed. The target is detected by the use of polarization technology, and the wavelet lifting algorithm with the advantage of less computation and higher processing speed is applied to decompose the polarization angle and degree of the polarization into high and low parts, then these two parts are fused with different rules to make the target edge contour distinguish from the low contrast background with full and clear details, which is more suitable for human eyes to recognize the target. A large number of target recognition experiments in low contrast environment and fusion results evaluation standards show that the proposed algorithm can effectively enhance the target recognition ratio, and its feasibility in low contrast environment is verified.