李壮, 杨夏, 于起峰. SAR图像中机场跑道自动检测方法研究[J]. 应用光学, 2011, 32(1): 49-53.
引用本文: 李壮, 杨夏, 于起峰. SAR图像中机场跑道自动检测方法研究[J]. 应用光学, 2011, 32(1): 49-53.
LI Zhuang, YANG Xia, YU Qi-feng. AAutomatic detection of airfield runways in SAR images[J]. Journal of Applied Optics, 2011, 32(1): 49-53.
Citation: LI Zhuang, YANG Xia, YU Qi-feng. AAutomatic detection of airfield runways in SAR images[J]. Journal of Applied Optics, 2011, 32(1): 49-53.

SAR图像中机场跑道自动检测方法研究

AAutomatic detection of airfield runways in SAR images

  • 摘要: 跑道检测通常由边缘检测和霍夫变换2个步骤组成。由于SAR图像中存在大量斑点噪声,使得边缘检测中存在大量虚假边缘,增加了霍夫变换的时间,降低了跑道检测的准确度,提出一种基于区域分割和距离变换的SAR图像中机场跑道自动检测的新方法。采用基于统计信息的方法增强跑道-背景的对比度,然后用二维直方图阈值分割方法分割图像,再通过距离变换对跑道-背景二值图进行处理,得到跑道中心线的大致分布,最后采用局部空间霍夫变换得到跑道参数。实验结果表明:该方法能够可靠检测出跑道,运算速度满足实时性要求。

     

    Abstract: To detect airport runway in SAR image automatically, a new algorithm is proposed based on region segmentation and distance transform. The statistic information is used to enhance the contrast between runways and background,and 2-D histogram method is used to segment the image. Then, distance transform and partial space Hough transform is utilized to detect the center line of runways. Experimental results show that the algorithm can extract runways in large complex SAR images with good real-time performance.

     

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