一种基于Gaussian-Hermite矩的SAR图像分割方法

图像分割在SAR图像处理中具有很重要的意义。文中提出了一种基于Gaussian-Hermite矩的SAR图像分割方法。该方法针对合成孔径雷达(SAR)图像斑点噪声对现有分割方法带来的影响,利用Gaussian-Hermite矩的不同阶矩并结合SAR图像特征将目标从含噪背景中分割出来。实验部分同时采用了仿真数据和实测SAR数据,通过与小波能量等4种方法的分割结果进行比较,显示出了该方法的有效性。

A Gaussian-Hermite Moments Algorithm for SAR Image Segmentation

SAR image segmentation is one of the most important tasks on SAR image processing.But the multiplication nature of the speckle noise in SAR images has been a troublesome problem in SAR images.In this paper,a SAR image segmentation approach based on Gaussian-Hermite moments is proposed.Because Gaussian-Hermite moments can better separate image features and enhance the object based on different modes.Different orders of Gaussian-Hermite moments are made use of as image features to extract objects from background scene.We use the even order moments equivalent to a filter to perform the segmentation in SAR image.The proposed algorithm is compared with other four algorithms on real SAR images(Figure 4) and simulation images(Figure 3).Experimental results show that the proposed method is effective to extract objects from background scene in SAR image and to restrain the speckle noise.