噪声抑制是红外图像处理中一个重要的研究课题，但常用的去噪算法会造成细节的损失。为有效地抑制噪声，同时保护边缘，在P-M扩散模型的基础上，提出了一种新的基于方向信息测度和边缘隶属度的各向异性扩散滤波算法。该算法的核心内容是将图像分为边缘区和非边缘区两个区域，对非边缘区采用常规P-M扩散方程完成噪声的滤除，对边缘区采用基于方向信息测度的非线性扩散方法，在平滑去噪的同时对边缘进行修整、增强。最终的仿真结果表明,该算法的峰值信噪比、均方误差、辐射分辨率等参数均优于常规算法，该算法具有良好的前景和实用价值。

Noise reduction is an important research topic of the infrared image processing，but the commonly used noise reduction methods will cause the loss of the details.In order to effectively reduce the noise and protect the edge at the same time，a new anisotropic diffusion algorithm based on the information measure and the edge membership is introduced. The core content of this algorithm is to divide the image into two areas，the edge area and the non-edge area. While the conventional P-M diffusion equation is used into the non-edge area to filter the noise，and the nonlinear diffusion equation based on the information measure is used into the edge area to filter the noise and enhance the edge. The final results show that this algorithms PSNR，MAE and radiometric resolution are better than the traditional algorithms. So this algorithm has practicality and potential application value.