红外空间图像中建筑物检测的分割方法

A. Gorobets
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引用次数: 1

摘要

本文描述了一种新的图像分割技术,特别是用于雷达或红外对地观测图像上的建筑物检测。该方法是基于大多数人造物体的特性,这些物体都是直线的,而且大多是直角的。开发的2D自适应图像滤波器有助于检测直边,即使给定的图像片段具有低对比度并且已经被极度噪声,此外,如果物体边缘被扭曲,例如,由于SAR方位通道的干扰,滤波器补偿不超过规定值的扭曲。没有图像光栅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可能目标集。这种方法可以作为神经网络的加法,也可以为训练数据集的准备提供帮助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Segmentation for detecting buildings in infrared space images
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.
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