为了在滤波的同时较好地保留边缘细节，提出一种基于像素点分类的激光主动成像混合滤波方法，将像素点根据其轮廓曲率进行分类，使用Lee滤波去除散斑噪声，使用模糊加权均值滤波器滤除其余混合噪声。定义一种轮廓点筛选方法，从含噪图像中提取候选轮廓点。将轮廓细化，剔除噪声引起的伪轮廓和强度较小的轮廓后，计算轮廓曲率，并根据轮廓曲率将图像上的像素点分为强信息点、弱信息点和无信息点。对于属于不同类的像素点，使用不同滤波参数的Lee和模糊加权均值滤波器进行滤波，使算法具备像素级的自适应性。实验结果表明，所提算法比Lee、Kuan和小波软阈值滤波有更好的去噪能力和轮廓细节保留能力。

In order to keep the detail information of edges while suppressing noise in laser active imaging, hybrid filter based on pixel classification is proposed. Based on contour curvature, the pixels are divided into different classes. Lee filter is used to suppress speckle noise and fuzzy weighted averaging filter is used to suppress other mixed noise. A contour point screening method is proposed to select candidate contour points from noisy image. Then the contours are thinned into single pixel. After eliminating the bogus contours brought by the noise and those that are comparatively week, the contour curvatures are calculated. According to the contour curvature, the pixels of the image are divided into different classes. For the pixels belonging to different classes, fuzzy weighted averaging filter and Lee filter with different filter parameters are used, which makes the proposed method own pixel-level adaptability. Experimental results indicate that the proposed method outperform the classical Lee, Kuan and wavelet soft-thresholding filter in denoising and keeping detail edge information.