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Improved balloon snake method for water boundary extraction in remote sensing images

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing Wuhan University, Wuhan 430079, China

  • Email：cnc@whu.edu.cn
  • Introduction：陈能成(1974—　)，男，教授,研究方向为对地观测传感网、时空大数据、动态实时网络GIS和位置智慧应用。E-mail：cnc@whu.edu.cn
CHEN Nengcheng,  
  • Affiliation：

    State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing Wuhan University, Wuhan 430079, China

LIU Dandan1,  
  • Affiliation：

    State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing Wuhan University, Wuhan 430079, China

DU Wenying1

Resümee

The traditional balloon snake model is free from the constraints of orthogonal grids compared with the topology-adaptive snake model and thus extracts water boundaries from high-resolution remote sensing images with more accuracy. However, this method cannot detect and handle topological conflict caused by islands in water. To solve this problem, an improved topology-adaptive balloon snake model, which is based on the traditional balloon snake model, is proposed. First, an original contour inside the target water body is manually set. Then, self-intersection detection is conducted each time prior to contour expansion. If holes cause topological conflict, curve deformation will be performed until the iteration stops. The data selected for this experiment were obtained from the GF-1 observing satellite images of three kinds of lakes and rivers, thus realizing the one-off accurate extraction of complex water from remote sensing images. Based on the results of our experiment, the proposed method can efficiently, correctly, and completely extract the boundaries of deeply concave regions and islands.

Schlüsselwort

remote sensing image;river island;boundary extraction;improved Balloon Snake;topological conflict

References

  1. 1.
    Abbas Q, Celebi M E and García IF. 2013.Breast mass segmentation using region-based and edge-based methods in a 4-stage multiscale system. Biomedical Signal Processing and Control, 8(2): 204–214
  2. 2.
    Bischoff S and Kobbelt L P. 2004. Parameterization-free active contour models with topology control. The Visual Computer, 20(4): 217–228
  3. 3.
    Cohen L D. 1991.On active contour models and balloons. CVGIP: Image Understanding, 53(2): 211–218
  4. 4.
    Filho P P R, Cortez P C, Barros A C D S and Albuquerque V H C D. 2014.Novel adaptive balloon active contour method based on internal force for image segmentation-A systematic evaluation on synthetic and real images. Expert Systems with Applications, 41(17): 7707–7721
  5. 5.
    Kass M, Witkin A and Terzopoulos D. 1988.Snakes: active contour models. International Journal of Computer Vision, 1(4): 321–331
  6. 6.
    Li Z B, Xu X Z, Le Y and Xu F Q. 2014.An improved balloon snake for HIFU image-guided system. Journal of Medical Ultrasonics, 41(3): 291–300
  7. 7.
    Lv H Y, Ma J F and Bao S L. 2006.A multi-object segmentation algorithm for snakes using inflating balloon model. Chinese Journal of Medical Imaging Technology, 22(3): 458–460
  8. 8.
    McInerney T and Terzopoulos D. 2000.T-snakes: topology adaptive snakes. Medical Image Analysis, 4(2): 73–91
  9. 9.
    Meng L K and Lv Q F. 2015.Improved orthogonal T-Snake model for complex water boundary extraction. Acta Geodaetica et CartographicaSinica, 44(6): 670–677
  10. 10.
    Meng W C, Zhu S L, Zhu B S, Cao W and Si Y B. 2011. Water area boundary extraction based on GVF Snake model and region growth. Journal of Geomatics Science and Technology, 28(4): 262–265
  11. 11.
    Meng W C. 2012. Intelligent Water Boundary Extraction from Remote Sensing Image. Zhengzhou: PLA Information Engineering University: 10–11
  12. 12.
    Wu H, Yi Y H, Wang X and Chen X W. 2006. A river bank extracting algorithm based on active contour model from high-resolution satellite images. Remote Sensing Technology and Application, 21(5): 407–413
  13. 13.
    Xu C Y and Prince J L. 1998.Snakes, shapes, and gradient vector flow. IEEE Transactions on Image Processing, 7(3): 359–369
  14. 14.
    Yang S W, Xue C S, Liu T and Li Y K. 2010.A method of small water information automatic extraction from TM remote sensing images.ActaGeodaetica et CartographicaSinica, 39(6): 611–617
  15. 15.
    Zhang R G, Liu K, Cai J H and Liu X J. 2012. Active contour model for deformable curves and surfaces. Beijing: National Defence Industry Press
  16. 16.
    Zheng S. 2010. An intensive restraint topology adaptive snake model and its application in tracking dynamic image sequence. Information Sciences, 180(16): 2940–2959
  17. 17.
    Zhou Y N, Zhu Z W, Shen Z F and Cheng X. 2012.Automatic extraction of coastline from TM image integrating texture and spatial elationship. Acta Scientiarum Naturalium Universitatis Pekinensis, 48(2): 273–279
  18. 18.
    Zhu S L, Meng W C and Zhu B S. 2013.Irregular water boundary extraction using GVF Snake. Journal of Remote Sensing, 17(4): 742–758

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