基于大数据量遥感图像的薄云去除

THE REMOVING CLOUDS METHOD BASED ON LARGE REMOTE SENSING IMAGE

对于带有薄云的大数据量遥感图像,提出了一种新的空域滤波去云方法.用这一方法对图像进行重采样、薄云识别、云的厚度估计,再使用拉普拉斯算子增强有云区域的对比度,并对不同厚度的云层分别降低不同的亮度,从而实现去云.然后进行图像恢复,得到跟原图像同样大小的去云后的图像.实验证明,这种方法速度快,占用计算机的内存少,得到的图像效果好.

As to the large remote sensing image with thin clouds, a new method of filtering in space domain is introduced. Firstly, the image is sampled, the thin clouds are recognized and their thickness is estimated. Secondly, the contrast is enhanced by using Laplacian in clouds area and the lightness is reduced according to their thickness. Finally, the image is recoverd and an image without thin clouds is obtained. The experiment proves this method is faster, uses less memory and gets better result.