• Journal of Geo-information Science
  • Vol. 22, Issue 2, 258 (2020)
Huixin HE1、1, Junfu FAN1、1、*, Wenhe CHEN1、1, Yuke ZHOU2、2, Peng ZHANG1、1, and Xiao YU1、1
Author Affiliations
  • 1School of Civil and Architectural Engineering, Shandong University of Technology, Zibo 255000, China
  • 1山东理工大学建筑工程学院,淄博 255000
  • 2Ecology Observing Network and Modeling Laboratory, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
  • 2中国科学院地理科学与资源研究所 生态系统网络观测与模拟院重点实验室,北京 100101
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    DOI: 10.12082/dqxxkx.2020.190270 Cite this Article
    Huixin HE, Junfu FAN, Wenhe CHEN, Yuke ZHOU, Peng ZHANG, Xiao YU. Extraction of Shaded Roads in High-Resolution Remote Sensing Imagery based on Brightness Compensation[J]. Journal of Geo-information Science, 2020, 22(2): 258 Copy Citation Text show less
    Flowchart of shaded roads extraction with brightness compensation method
    Fig. 1. Flowchart of shaded roads extraction with brightness compensation method
    Image preprocessing of linear stretch and bilateral filter
    Fig. 2. Image preprocessing of linear stretch and bilateral filter
    Shadow extraction on HSI space with threshold segmentation
    Fig. 3. Shadow extraction on HSI space with threshold segmentation
    Brightness compensation over shadow areas
    Fig. 4. Brightness compensation over shadow areas
    Brightness compensation over shadow areas for the shaded road extraction
    Fig. 5. Brightness compensation over shadow areas for the shaded road extraction
    Comparison of the K-means and K-means++ algorithms in extracting unshaded roads with threshold segmentation
    Fig. 6. Comparison of the K-means and K-means++ algorithms in extracting unshaded roads with threshold segmentation
    Definition of shape endpoints in outline reparation method
    Fig. 7. Definition of shape endpoints in outline reparation method
    Data source for the verification experiment
    Fig. 8. Data source for the verification experiment
    Results of unshaded roads extraction with threshold segmentation in HSI space and K-means algorithm
    Fig. 9. Results of unshaded roads extraction with threshold segmentation in HSI space and K-means algorithm
    Shaded roads extraction and preprocessing
    Fig. 10. Shaded roads extraction and preprocessing
    Result of shaded roads extraction based on the brightness compensation method
    Fig. 11. Result of shaded roads extraction based on the brightness compensation method
    Comparison of brightness compensation method and traditional shadow coefficient amendment method in rough extraction of shaded roads
    Fig. 12. Comparison of brightness compensation method and traditional shadow coefficient amendment method in rough extraction of shaded roads
    郊区道路市区道路
    本文方法传统方法本文方法传统方法
    TP/个60 32853 14587 63673 447
    FN/个1969664023 10737 296
    FP/个13 63161 03119 36746 683
    完整率/%96.8488.8979.1366.32
    正确率/%81.5746.5581.9061.14
    检测质量/%79.4543.9867.3646.65
    Table 1. Evaluation of the shaded roads extraction results
    Huixin HE, Junfu FAN, Wenhe CHEN, Yuke ZHOU, Peng ZHANG, Xiao YU. Extraction of Shaded Roads in High-Resolution Remote Sensing Imagery based on Brightness Compensation[J]. Journal of Geo-information Science, 2020, 22(2): 258
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