针对P M方程、Shock滤波器和相干增强扩散等基本偏微分方程模型的不足，以及现有的融合方法难以对复杂的路面图像取得满意的增强效果的问题，提出了将以上3种基本模型加以融合的新融合方法。该方法首先分析了相干增强扩散中扩散速度与局部结构一致性强弱的对应关系，并在假设图像不含噪声的基础上，设计了以梯度和局部结构一致性强弱作为参数的权函数，用来对3种基本模型进行加权融合；然后根据路面图像中的噪声及裂缝信息的特点，通过对基本模型和权函数的改进来对无噪模型进行推广，使之适合于处理复杂的路面图像，另外对模型中涉及到的一些主要参数也进行了详细的讨论。理论分析和实验结果表明，该新算法在路面图像的去噪、裂缝边缘锐化和增强裂缝的流式结构等方面均可取得良好的效果。

Since P M diffusion,Shock filter,coherence enhancing diffusion and their fusing models in existence can not enhance road surface images well, a new model fused by the 3 basic PDE models is proposed. First the relationship between the diffusion strength of coherence enhancing diffusion and the degree of consistency of local directional structure is analyzed, and on the assumption that images are without noise, 3 weight functions depending on the local gradients and the degree of consistency of local directional structure are designed, and the 3 basic PDE models are fused together by the 3 weight functions. Then according to the characteristics of road