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Segmentation for detecting buildings in infrared space images

机译:在红外空间图像中检测建筑物的分割

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The given work describes a new technique of image segmentation, in particular for building detection on radar or infrared Earth-observation images. The method is based on property of most man-made objects which consist in straight edges and mostly right angles. The developed 2D adaptive image filter assists to detect straight edges even if given image fragment has a low contrast and has been extremely noised, in addition, if an object edge has been distorted, for example, by interference in the SAR azimuth channel, the filter compensates for distortions which do not exceed the specified value. The next processing of line-segment list without image raster works faster and allows detecting a relatively small set of possible targets. This approach could be used as addition for neural networks as well as provide assistance in preparing of training data set.
机译:给出的工作描述了一种图像分割的新技术,特别是用于在雷达或红外地球观测图像上进行建筑物检测的技术。该方法基于大多数人造物体的特性,这些人造物体包括直边和大部分为直角。即使给定的图像片段对比度低且受到极大的干扰,开发的2D自适应图像滤波器也有助于检测直边,此外,如果物体边缘已失真,例如由于SAR方位角通道中的干扰而导致失真,则该滤波器补偿不超过指定值的失真。没有图像栅格的线段列表的下一个处理工作更快,并且允许检测相对较小的一组可能的目标。这种方法可以用作神经网络的补充,并在准备训练数据集方面提供帮助。

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