红外图像存在信噪比低、对比度差的问题，在目标辐射强度低、距离远以及恶劣天气状况下尤为严重。为了提高图像信噪比，提出一种红外图像中的自适应维纳滤波噪声抑制算法。算法突破了维纳滤波要求未退化图像和噪声功率谱已知的技术瓶颈，基于 Canny边缘检测算子构建了平滑区域噪声方差的邻域估计准则，实现了红外图像噪声的自适应抑制。实验表明：该算法能根据噪声水平自适应调整滤波参数，抑制噪声的同时有效保持了边缘细节信息，适用于红外实时成像系统。

The Signal-to-Noise Ratio (SNR) and contrast are low in infrared image, which is serious in low target radiation, long detecting distance and bad weather. For enhancing the SNR of infrared image, an adaptive Wiener filtering noise reduction algorithm is proposed. In this algorithm, the technical bottleneck that power spectrums of undegraded image and noise need be known in traditional Wiener filtering is broken. A neighborhood estimation criterion of noise variance of smoothness region is proposed, and the noise adaptive reduction of infrared image is achieved. Experimental results show the proposed algorithm can adjust filtering parameters adaptively, remove the noise, and in the mean time effectively preserve the information of edge and detail, which can be applied to infrared real-time imaging system.