高分辨率遥感图像灾区建筑物检测

发布时间：2018-04-25 05:30

  本文选题：建筑物检测 + 图像分割　； 参考：《数据采集与处理》2017年02期

【摘要】：在遥感图像中,灾区建筑物的检测对灾情获取和灾后应急救援具有重要意义。针对灾区高分辨率遥感图像中建筑物检测的问题,提出了一种改进的基于形态学特征的多方向和多尺度分割方法,以实现灾区建筑物的自动化检测。首先将形态学算子的重建、粒度和方向等性质整合到建筑物的亮度、大小和对比度等特征中,对遥感图像进行初步的分割并提取高亮和高对比度的建筑物,然后结合图像的区域边缘信息,进一步提取潜在的建筑物。实验结果表明,所提方法对灾区高分辨率图像中的建筑目标有较高的检测率和较低的误检率。
[Abstract]:In remote sensing images, the detection of buildings in disaster areas is of great significance to disaster situation acquisition and emergency rescue. In order to solve the problem of building detection in high resolution remote sensing images of disaster areas, an improved multi-direction and multi-scale segmentation method based on morphological features is proposed to realize the automatic detection of buildings in disaster-stricken areas. Firstly, the reconstruction, granularity and direction of the morphological operator are integrated into the luminance, size and contrast of the building to segment the remote sensing image and extract the high-contrast and high-contrast buildings. Then combined with the region edge information of the image, the potential buildings are further extracted. The experimental results show that the proposed method has higher detection rate and lower false detection rate for building targets in high resolution images of disaster areas.
【作者单位】： 南京理工大学计算机科学与工程学院;
【基金】：国家自然科学基金(61003108/61371168)资助项目 公安部应用创新计划(2013YYCXGASS097)资助项目
【分类号】：TP751

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