基于云影距离模型的遥感图像多尺度融合算法

Remote sensing image fusion using MGA based on cloud and shadow distance model

为了对含云及云影遥感图像上的云影进行有效消除,首先构建了遥感云影成像距离模型,并依据遥感云影距离模型,提出了一种新的云影识别算法,用来对有云遥感图像中的云层和阴影进行检测与识别,并生成融合区域图;然后在融合区域图的基础上,提出了一种多尺度图像融合算法,用来消除云影,即先对源图像进行多尺度几何分解,得到源图像的粗糙和细节分量,然后对云影区域和非云影区域分别采用不同的融合策略进行处理得到融合图像。仿真实验结果表明,该新融合算法不仅对薄云的消除效果非常好,而且对厚云及阴影的消除效果也非常好,且不会产生衔接边缘。

In order to remove clouds and shadows more effectively, cloud and shadow distance model is established in this paper at first. And a novel method is proposed for detecting and distinguishing clouds and shadows to form a fusion region map based on this model. After getting the fusion region map, a new image fusion method based on MGA （muhiscale geometric analysis） is proposed for removing clouds and shadows. This new image fusion method decomposes the source images and obtains the coarse and detail band parts, then fuses the different regions by using different fusion rules. Experiments show that this new image fusion method can not only remove thin clouds and shadows, but also have much better performance for thick clouds and shadows without any join edge.