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陶思然. 顾及梯度和彩色信息的高分辨率影像道路分割[J]. 科学技术与工程, 2019, 19(31): 263-269.
Tao Si-ran.Road Segmentation of High-spatial Resolution Remote Sensing Images by Considering Gradient and Color Information[J].Science Technology and Engineering,2019,19(31):263-269.
顾及梯度和彩色信息的高分辨率影像道路分割
Road Segmentation of High-spatial Resolution Remote Sensing Images by Considering Gradient and Color Information
投稿时间:2019-02-26  修订日期:2019-07-12
DOI:
中文关键词:  梯度-灰度相关性连接  边界验证  高分辨率道路影像  彩色信息  梯度值
英文关键词:gradient-grayscale correlation connection  boundary validation  high-resolution road images  color information  gradient values
基金项目:国家863计划资助项目(2007AA092102)、高分辨率对地观测重大专项(07-Y30A05-9001-12/13)
  
作者单位
陶思然 天津市测绘院
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中文摘要:
      针对高分辨率影像中道路灰度值分布不均,“同谱异物”现象难以用简单阈值分割,以及对不同传感器、不同分辨率影像提取效果不一样等问题,提出了一种顾及空间梯度信息和彩色信息的道路阈值分割方法。利用高分辨率影像的多种特征,将梯度值和灰度值进行
英文摘要:
      This paper presents a road threshold segmentation method that taking into account spatial gradient information and color information in order to solve the problem of uneven distribution of road gray values in high resolution images and the difficulty of segmentation of the different things with the same spectrum with simple thresholds, and it has different effects on the extraction of high-resolution road images from different sensors and different resolutions. The gradient value and gray value are combined to get the correlation connection factor, and the original road image is transformed into HSI color space to segment the gray consistency region of the road, and the segmentation results are verified by gradient value. Finally, the validation results and the segmentation results of correlation connectivity factors are fused to remove the non-road information, and filter the non-road information to extract the accurate road. Using images of different sensors and different resolution to experiment. The results show that the algorithm can well solve the above problems and strong adaptability. By comparison with the existing method, the superiority of the proposed algorithm in precision is verified.
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