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Optimal edge detection and edge localization in complex SAR images with correlated speckle

机译:具有相关斑点的复杂SAR图像中的最佳边缘检测和边缘定位

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摘要

The authors develop optimal criteria for detection and localization of step edges in single look complex (SLC) synthetic aperture radar (SAR) images. By working on complex data rather than intensity images, they can easily take the speckle autocorrelation into account, obtain more accurate estimates of local mean reflectivities, and thus achieve better edge detection and edge localization than with operators known from the literature. Algorithms for the two-dimensional (2D) implementation of the methods are proposed, and some segmentation results are shown.
机译:作者开发了用于检测和定位单眼复杂(SLC)合成孔径雷达(SAR)图像中台阶边缘的最佳标准。通过处理复杂的数据而不是强度图像,它们可以轻松地考虑散斑自相关,获得更准确的局部平均反射率估计值,从而获得比文献中已知的算符更好的边缘检测和边缘定位。提出了该方法的二维(2D)实现算法,并显示了一些分割结果。

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