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SAR image segmentation by morphological methods

机译:通过形态学方法进行SAR图像分割

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摘要

The presence of speckle, which may be modeled as a strong multiplicative noise, makes the segmentation of synthetic aperture radar (SAR) images very difficult. The usual gradient operators yield poor results, but robust operators have been developed specifically for this kind of images. From the edge strength map ('gradient image') created by such an operator, closed skeleton boundaries running through local maxima must be extracted. This can be achieved with the watershed algorithm. However, to reduce the number of false edges, the algorithm must be made less sensitive to speckle. In this article, we compare two different approaches - watershed thresholding and basin dynamics - and propose a new algorithm for the computation of edge dynamics. The improvement brought by basin and edge dynamics is illustrated on ERS-1 images of an agricultural zone.
机译:斑点的存在,其可以被建模为强乘法噪声,使得合成孔径雷达(SAR)图像的分割非常困难。通常的梯度运算符产生差的结果,但已经专门为这种图像开发了强大的运营商。来自由这样的操作员创建的边缘强度图('梯度图像'),必须提取通过本地最大值运行的闭合骨架边界。这可以通过流域算法实现。但是,为了减少错误边缘的数量,必须对散斑敏感算法。在本文中,我们比较了两种不同的方法 - 流域阈值和盆地动力学 - 并提出了一种新的边缘动力学计算算法。盆地和边缘动态带来的改进在农业区的ERS-1图像上说明了。

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