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Road extraction using modified dark channel prior and neighborhood FCM in foggy aerial images

  • Wang Fengping
  • Wang Weixing
Article

Abstract

It is still a challenge to accomplish road extraction from the aerial images in foggy weather. In this paper, a road extraction method based on modified dark channel prior and improved neighborhood FCM (Fuzzy C-means) is proposed for foggy aerial images. Firstly, a defogging method based on modified dark channel prior is applied to increase the image contrast and highlight the road areas. In the proposed method, a region filtering function is designed to generate the dark channel image, and an adaptive parameter is set up to adjust the defogging degree automatically. Secondly, an improved neighborhood FCM algorithm is studied to extract the road area. According to the neighborhood feature, the spatial distance and the gray level difference can be calculated as the parameters of the objective function which can eliminate noise and promote the detection accuracy. Finally, an image post-processing procedure is utilized to connect the road gaps and remove the false road areas. The experimental results verify that the proposed method can achieve satisfied road extraction effect both on completeness and correctness.

Keywords

Road extraction Foggy aerial image Dark channel prior Neighborhood fuzzy C-means 

Notes

Acknowledgments

The authors would like to thank the anonymous reviewers for their valuable remarks and suggestions. This work was supported by the Doctoral Dissertation Foster Fund of Chang’an University (Grant No. 310824165003), and the International Cooperation Project in China (Grant No. 2013KW03).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Information EngineeringChang’an UniversityXi’anPeople’s Republic of China

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