基于支持向量机的遥感影像薄云去除方法

Thin cloud removing approach of remote sensing image based on support vector machine

提出了一种基于支持向量机的遥感影像薄云去除方法。利用支持向量机对边缘点的极强捕捉能力,将含云遥感影像进行多尺度分解,获得不同尺度上的变换系数,再结合方向滤波器组得到丰富的高频信息。采用自适应阈值的图像增强方法处理这片区域,重构时通过对高频区域的增强和低频区域的抑制,得到去云图像。实验结果表明,采用该方法能有效地去除遥感影像中的薄云。

A new thin cloud removing approach of remote sensing image based on support vector machine is introduced. Firstly, remote sensing image is decomposed in multi-scale by using strong edge capture ability of support vector machine, and the coefficients in different scales are obtained. Then abundant high frequency information is obtained by combining with directional filter bank. The high frequency information is enhanced based on adaptive threshold. Reconstructed image is obtained through enhancing coefficients of high frequency and suppressing coefficients of low frequency. Experiments show that thin cloud is removed efficiently based on the method.