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International Journal of Aerospace Engineering
Volume 2017, Article ID 1793212, 7 pages
https://doi.org/10.1155/2017/1793212
Research Article

Edge Detection in UAV Remote Sensing Images Using the Method Integrating Zernike Moments with Clustering Algorithms

1Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming 650093, China
2Kunming Surveying and Mapping Institute, Kunming 650051, China

Correspondence should be addressed to Liang Huang; moc.361@gnailgnauhmk

Received 18 September 2016; Revised 5 January 2017; Accepted 18 January 2017; Published 15 February 2017

Academic Editor: Paul Williams

Copyright © 2017 Liang Huang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. S. Cao, J. Jiang, G. Zhang, and Y. Yuan, “An edge-based scale- and affine-invariant algorithm for remote sensing image registration,” International Journal of Remote Sensing, vol. 34, no. 7, pp. 2301–2326, 2013. View at Publisher · View at Google Scholar · View at Scopus
  2. Y. Hu, J. Chen, D. Pan, and Z. Hao, “Edge-guided image object detection in multiscale segmentation for high-resolution remotely sensed imagery,” IEEE Transactions on Geoscience and Remote Sensing, vol. 54, no. 8, pp. 4702–4711, 2016. View at Publisher · View at Google Scholar · View at Scopus
  3. X. Huang, L. Zhang, and P. Li, “Classification of very high spatial resolution imagery based on the fusion of edge and multispectral information,” Photogrammetric Engineering & Remote Sensing, vol. 74, no. 12, pp. 1585–1596, 2008. View at Publisher · View at Google Scholar · View at Scopus
  4. S. Klonus, D. Tomowski, M. Ehlers, P. Reinartz, and U. Michel, “Combined edge segment texture analysis for the detection of damaged buildings in crisis areas,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 5, no. 4, pp. 1118–1128, 2012. View at Publisher · View at Google Scholar · View at Scopus
  5. J. X. Wang, X. Y. Qi, and X. W. Li, “Edge and local energy NSCT based remote sensing image fusion,” Journal of the Graduate School of the Chinese Academy of Sciences, vol. 26, no. 5, pp. 657–662, 2009. View at Google Scholar
  6. A. Kiani and M. R. Sahebi, “Edge detection based on the Shannon Entropy by piecewise thresholding on remote sensing images,” IET Computer Vision, vol. 9, no. 5, pp. 758–768, 2015. View at Publisher · View at Google Scholar · View at Scopus
  7. H. Vishwakarma and S. Katiyar, “Comparative study of edge detection algorithms on the remote sensing images using matlab,” International Journal of Advances in Engineering Research (IJAER), vol. 2, no. 6, 2011. View at Google Scholar
  8. B. Kaur and A. Garg, “Mathematical morphological edge detection for remote sensing images,” in Proceedings of the 3rd International Conference on Electronics Computer Technology (ICECT '11), vol. 6, pp. 324–327, April 2011. View at Publisher · View at Google Scholar · View at Scopus
  9. X. Guan and Z. Guan, “Edge detection of high resolution remote sensing imagery using wavelet,” in Proceedings of the International Conferences on Info-Tech and Info-Net (ICII '01), vol. 301, pp. 302–307, IEEE, Beijing, China, November 2001. View at Publisher · View at Google Scholar · View at Scopus
  10. G.-B. Xu, G.-Y. Zhao, L. Yin, Y.-X. Yin, and Y.-L. Shen, “A CNN-based edge detection algorithm for remote sensing image,” in Proceedings of the Chinese Control and Decision Conference 2008 (CCDC '08), pp. 2558–2561, July 2008. View at Publisher · View at Google Scholar · View at Scopus
  11. A. Jubai, B. Jing, and J. Yang, “Combining fuzzy theory and a genetic algorithm for satellite image edge detection,” International Journal of Remote Sensing, vol. 27, no. 14, pp. 3013–3024, 2006. View at Publisher · View at Google Scholar · View at Scopus
  12. J. Xi and J.-Z. Zhang, “Edge detection from remote sensing images based on Canny operator and Hough transform,” Advances in Intelligent and Soft Computing, vol. 141, pp. 807–814, 2012. View at Publisher · View at Google Scholar · View at Scopus
  13. K. F. Huang, X. Q. Yu, and L. Huang, “Edge detection method for remote sensing image based on PCNN and LOG operator,” Journal of Guizhou University, vol. 32, no. 5, pp. 29–32, 2015. View at Google Scholar
  14. L. Huang, Y. Fang, X. Zuo, X. Yu, and S. Lu, “Edge information detection of remote sensing image based on two-dimensional Otsu algorithm,” Journal of Information and Computational Science, vol. 10, no. 16, pp. 5381–5390, 2013. View at Publisher · View at Google Scholar · View at Scopus
  15. N. S. Mishra, S. Ghosh, and A. Ghosh, “Fuzzy clustering algorithms incorporating local information for change detection in remotely sensed images,” Applied Soft Computing, vol. 12, no. 8, pp. 2683–2692, 2012. View at Publisher · View at Google Scholar · View at Scopus
  16. X. P. Feng and T. F. Zhang, “Comparison of four clustering methods,” Microcomputer & Its Applications, vol. 29, no. 16, pp. 1–3, 2010. View at Google Scholar
  17. S. Xu, J. Liu, Y. Wang, and M. Hu, “Sub-pixel edge detection of color image based on principal axis analysis and EDISON-Zernike moment,” Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument, vol. 29, no. 11, pp. 2272–2277, 2008. View at Google Scholar · View at Scopus
  18. X. H. Ding, S. X. Deng, Y. Y. Yang, and Q. C. Zhao, “Sub-pixel edge detection based on spatial moments and Zernike moments,” Journal of Applied Sciences, vol. 22, no. 2, pp. 191–194, 2004. View at Google Scholar
  19. S. Ghosal and R. Mehrotra, “Orthogonal moment operators for subpixel edge detection,” Pattern Recognition, vol. 26, no. 2, pp. 295–306, 1993. View at Publisher · View at Google Scholar · View at Scopus
  20. J.-W. Cui and J.-B. Tan, “Algorithm for edge subpixel location based on Zernike moment,” Guangxue Jishu/Optical Technique, vol. 31, no. 5, pp. 779–785, 2005. View at Google Scholar · View at Scopus
  21. R. Medina-Carnicer, R. Muñoz-Salinas, A. Carmona-Poyato, and F. J. Madrid-Cuevas, “A novel histogram transformation to improve the performance of thresholding methods in edge detection,” Pattern Recognition Letters, vol. 32, no. 5, pp. 676–693, 2011. View at Publisher · View at Google Scholar · View at Scopus