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Mathematical Problems in Engineering
Volume 2013, Article ID 518747, 7 pages
http://dx.doi.org/10.1155/2013/518747
Research Article

Nonlocal Variational Model for Saliency Detection

1Department of Mathematics & KLDAIP, Chongqing University of Arts and Sciences, Yongchuan, Chongqing 402160, China
2College of Mathematics and Statistics, Chongqing Technology and Business University, Chongqing 400067, China
3College of Mathematics and Physics, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Received 4 June 2013; Accepted 25 August 2013

Academic Editor: Baocang Ding

Copyright © 2013 Meng Li 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. H. Fu, Z. Chi, and D. Feng, “Attention-driven image interpretation with application to image retrieval,” Pattern Recognition, vol. 39, no. 9, pp. 1604–1621, 2006. View at Publisher · View at Google Scholar · View at Scopus
  2. C. Guo and L. Zhang, “A novel multiresolution spatiotemporal saliency detection model and its applications in image and video compression,” IEEE Transactions on Image Processing, vol. 19, no. 1, pp. 185–198, 2010. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  3. K. Rapantzikos, N. Tsapatsoulis, Y. Avrithis, and S. Kollias, “Bottom-up spatiotemporal visual attention model for video analysis,” IET Image Processing, vol. 1, no. 2, pp. 237–248, 2007. View at Publisher · View at Google Scholar · View at Scopus
  4. L. Itti, C. Koch, and E. Niebur, “A model of saliency-based visual attention for rapid scene analysis,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 20, no. 11, pp. 1254–1259, 1998. View at Publisher · View at Google Scholar · View at Scopus
  5. S. Frintrop, M. Klodt, and E. Rome, “A real-time visual attention system using integral images,” in Proceedings of the International Conference on computer Vision Systems, 2007.
  6. Y. F. Ma and H. J. Zhang, “Contrast-based image attention analysis by using fuzzy growing,” in Proceedings of the 11th ACM International Conference on Multimedia (MM '03), pp. 374–381, November 2003. View at Scopus
  7. R. Achanta, F. Estrada, P. Wils, and S. Süsstrunk, “Salient region detection and segmentation,” in Proceedings of the International Conference on Computer Vision Systems, pp. 66–75, 2008.
  8. R. Achanta, S. Hemami, F. Estrada, and S. Süsstrunk, “Frequency-tuned salient region detection,” in Proceedings of the International on Computer Vision and Pattern Recognition, pp. 1597–1604, 2009.
  9. X. Hou and L. Zhang, “Saliency detection: a spectral residual approach,” in Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '07), June 2007. View at Publisher · View at Google Scholar · View at Scopus
  10. T. Liu, J. Sun, N. N. Zheng, X. Tang, and H. Y. Shum, “Learning to detect a salient object,” in Proceedings of the 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR '07), June 2007. View at Publisher · View at Google Scholar · View at Scopus
  11. C. Guo, Q. Ma, and L. Zhang, “Spatio-temporal saliency detection using phase spectrum of quaternion fourier transform,” in Proceedings of the 26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR '08), June 2008. View at Publisher · View at Google Scholar · View at Scopus
  12. S. Feng, D. Xu, and X. Yang, “Attention-driven salient edge(s) and region(s) extraction with application to CBIR,” Signal Processing, vol. 90, no. 1, pp. 1–15, 2010. View at Publisher · View at Google Scholar · View at Scopus
  13. J. Harel, C. Koch, and P. Perona, “Graph-based visual saliency,” Advances in Neural Information Processing Systems, vol. 19, pp. 545–552, 2007. View at Google Scholar
  14. N. D. B. Bruce and J. K. Tsotsos, “Saliency, attention and visual search: an information theoretic approach,” Journal of Vision, vol. 9, no. 3, article 5, 2009. View at Publisher · View at Google Scholar · View at Scopus
  15. Y. Fang, W. Lin, B. S. Lee, C. T. Lau, Z. Chen, and C. W. Lin, “Bottom-up saliency detection model based on human visual sensitivity and amplitude spectrum,” IEEE Transactions on Multimedia, vol. 14, no. 1, pp. 187–198, 2012. View at Publisher · View at Google Scholar · View at Scopus
  16. C. Koch and S. Ullman, “Shifts in selective visual attention: towards the underlying neural circuitry,” Human Neurobiology, vol. 4, no. 4, pp. 219–227, 1985. View at Google Scholar · View at Scopus
  17. H. C. Li, P. Z. Fan, and M. K. Khan, “Context-adaptive anisotropic diffusion for image denoising,” Electronics Letters, vol. 48, no. 14, pp. 827–829, 2012. View at Publisher · View at Google Scholar
  18. A. Kuijper, “Image analysis using p-Laplacian and geometrical PDEs,” Proceedings in Applied Mathematics and Mechanics, vol. 7, no. 1, pp. 1011201–1011202, 2007. View at Publisher · View at Google Scholar
  19. Y. Zhan, “The nonlocal p-Laplacian evolution for image interpolation,” Mathematical Problems in Engineering, vol. 2011, Article ID 837426, 11 pages, 2011. View at Publisher · View at Google Scholar · View at MathSciNet
  20. Q. Xin, C. Mu, and M. Li, “The Lee-Seo model with regularization term for bimodal image segmentation,” Mathematics and Computers in Simulation, vol. 81, no. 12, pp. 2608–2616, 2011. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  21. G. Aubert, J. F. Aujol, and L. Blanc-Féraud, “Detecting codimension-two objects in an image with Ginzburg-Landau models,” International Journal of Computer Vision, vol. 65, no. 1-2, pp. 29–42, 2005. View at Publisher · View at Google Scholar · View at Scopus
  22. H. Grossauer and O. Scherzer, “Using the complex Ginzburg-Landau equation for digital inpainting in 2D and 3D,” Lecture Notes in Computer Science, vol. 2695, pp. 225–236, 2003. View at Google Scholar · View at Scopus
  23. F. Andreu, J. M. Mazón, J. D. Rossi, and J. Toledo, “A nonlocal p-Laplacian evolution equation with Neumann boundary conditions,” Journal de Mathématiques Pures et Appliquées, vol. 90, no. 2, pp. 201–227, 2008. View at Publisher · View at Google Scholar · View at MathSciNet
  24. V. L. Ginzburg and L. D. Landau, “On the theory of superconductivity,” Zhurnal Eksperimentalnoi i Teoreticheskoi Fiziki, vol. 20, pp. 1064–1082, 1950. View at Google Scholar
  25. M. Ipsen and P. G. Sørensen, “Finite wavelength instabilities in a slow mode coupled complex Ginzburg-Landau equation,” Physical Review Letters, vol. 84, no. 11, pp. 2389–2392, 2000. View at Google Scholar · View at Scopus
  26. L. Ambrosio and N. Dancer, Calculus of Variations and Partial Differential Equations: Topics on Geometrical Evolution Problems and Degree Theory, Springer, Berlin, Germany, 2000. View at Publisher · View at Google Scholar · View at MathSciNet
  27. F. Li, C. Shen, and L. Pi, “A new diffusion-based variational model for image denoising and segmentation,” Journal of Mathematical Imaging and Vision, vol. 26, no. 1-2, pp. 115–125, 2006. View at Publisher · View at Google Scholar · View at MathSciNet
  28. Y. Zhai, D. Zhang, J. Sun, and B. Wu, “A novel variational model for image segmentation,” Journal of Computational and Applied Mathematics, vol. 235, no. 8, pp. 2234–2241, 2011. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  29. M. P. Bendsoe, “Variable-topology optimization: status and challenges,” in Proceedings of the European Conference on Computational Mechanics Wunderlich, W. Wunderlich, Ed., Munich, Germany, 1999.