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Line Segment Detection of Urban Area in SAR Images Based on Improved Gray Hough Transform

机译:基于改进的灰色霍夫变换的SAR图像市区线段检测

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As one of important applications in Synthetic Aperture Radar (SAR) images, the recognition of urban area has received considerable attentions in remote sensing. The extraction of line segment is very critical technology to recognize the urban area because many objects such as streets and buildings are line segment. The common method to extract line segment is Hough transform, but most of the previous methods are based on binary images. So we have to select a threshold to binarizate the image, but at most time we can not determine the threshold properly, resulting in the lost of useful information. To solve the problem, an improved Hough transform algorithm on gray level, which can make the extraction of line segment independent of the noise and the length of line segment, is proposed. The approach is validated by the analysis of SAR images.
机译:作为合成孔径雷达(SAR)图像的重要应用之一,城市区域的识别在遥感领域受到了广泛的关注。线段的提取是识别市区的非常关键的技术,因为许多对象(例如街道和建筑物)都是线段。提取线段的常用方法是霍夫变换,但是大多数以前的方法都是基于二进制图像。因此,我们必须选择一个阈值来对图像进行二值化处理,但是大多数时候我们无法正确确定阈值,从而导致有用信息的丢失。为了解决该问题,提出了一种改进的灰度霍夫变换算法,该算法可使线段的提取与噪声和线段的长度无关。通过对SAR图像的分析验证了该方法。

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