为有效去除三维网格模型中的噪声，提出一种用于网格去噪的自适应双边滤波 器． 首先，利用体积积分不变量对三维网格模型进行特征检测，估计出局部的特征强度，然 后根据特征强度自适应地调整双边滤波器的滤波参数． 通过自适应的参数优化，对于不同 特征强度的区域，自适应双边滤波器采用更具针对性的去噪策略，从而进一步提高了去噪 性能． 实验结果表明，相比于双边滤波器，所提出的自适应双边滤波器在去除噪声的同时， 能够更好地保持三维网格模型的细节特征，去噪后得到的网格模型与原始模型的客观差 值测度平均降低了 0． 0332．

In this paper，an adaptive bilateral filter is proposed to remove noises in 3D mesh models． Firstly，the feature detection of 3D mesh models is performed on the basis of the volume integral invariant，and the local feature strength is estimated． Then，the proposed filter adaptively adjusts the denoising parameters in the bilateral filter according to the local feature strength． Through the adaptive optimization of parameters，the proposed filter provides targeted denoising strategies for the regions with different feature strength，thus further improving the denoising performance． Experimental results reveal that，in comparison with common bilateral filters，the proposed adaptive bilateral filter achieves a superior performance in preserving the sharp features of 3D mesh models during the denoising，and the objective distance measure between the denoised mesh model and the original model is averagely reduced by 0. 0332．