红外偏振图像的仿真

为了在获得真实偏振图像之前获得偏振图像，采用仿真的方法进行了实验研究，即先通过实验获得各种物体的偏振度建立一个偏振数据库并进行理论研究论证，再利用K-均值聚类算法对红外图像中的物体进行聚类，最后将聚类后的图像通过计算得到偏振图像。结果表明，得到的仿真偏振图像效果很明显，能够很好地区分人造物和自然物，从而验证了仿真算法的可行性。图像仿真对于更好、更方便地研究物体的偏振特性和建立偏振数据库有着非常重要的意义。

Simulation of infrared polarization images

In order to obtain polarization images without true polarization images, firstly, the degree of polarization of various objects were found in experiments, and a database of degree of polarization was built. Then, objects in the infrared images were classified by means of K-means clustering algorithm. Finally, the polarization images were calculated from the clustering images. The results verify the simulation algorithm is feasible. The effect of the simulated images is good, it is easy to distinguish artificial object from natural objects. Image simulation is important for better and more convenient research of polarization properties of objects and the establishment of a database of polarization.