This work presents a method to automatically detect and remove shadows in urban aerial images and its application in an aerospace remote monitoring system requiring near real-time processing. Our detection method generates shadow masks and is accelerated by GPU programming. To obtain the shadow masks, we converted images from RGB to CIELCh model, calculated a modified Specthem ratio, and applied multilevel thresholding. Morphological operations were used to reduce shadow mask noise. The shadow masks are used in the process of removing shadows from the original images using the illumination ratio of the shadow/non-shadow regions. We obtained shadow detection accuracy of around 93% and shadow removal results comparable to the state-of-the-art while maintaining execution time under real-time constraints.

这项工作提出了一种自动检测和去除城市空中图像中的阴影的方法，并将其应用在需要近实时处理的航空远程监控系统中。我们的检测方法会生成阴影蒙版，并通过GPU编程进行加速。为了获得荫罩，我们将图像从RGB转换为CIELCh模型，计算了修改后的Specthem比率，并应用了多级阈值。使用形态学操作来减少荫罩噪声。在使用阴影/非阴影区域的照度比从原始图像中去除阴影的过程中，将使用荫罩。我们获得了大约93％的阴影检测精度，并且阴影去除效果与最新技术相当，同时在实时约束下保持了执行时间。