J Opt Soc Am A Opt Image Sci Vis. 2023 May 1;40(5):859-866. doi: 10.1364/JOSAA.488138.
With the development of infrared polarization sensors, image enhancement algorithms have been developed. Although using polarization information quickly distinguishes man-made objects from natural backgrounds, cumulus clouds would become detection noise because of their similar characteristics to targets in the sky scene. In this paper, we propose an image enhancement algorithm based on polarization characteristics and the atmospheric transmission model. The algorithm utilizes the principle of polarization imaging and atmospheric transmission theory to enhance the target in the image while suppressing the interference of clutter. We compare with other algorithms through the data we collected. The experimental results show that our algorithm significantly improves the target brightness and reduces clutter at the same time with real-time performance.
随着红外偏振传感器的发展，已经开发出了图像增强算法。虽然使用偏振信息可以快速区分人造物体和自然背景，但由于积云与天空场景中的目标具有相似的特征，它们可能会成为检测噪声。在本文中，我们提出了一种基于偏振特性和大气传输模型的图像增强算法。该算法利用偏振成像原理和大气传输理论，在增强图像中目标的同时抑制杂波干扰。我们通过收集到的数据与其他算法进行了比较。实验结果表明，我们的算法在具有实时性的同时，显著提高了目标的亮度并减少了杂波。
