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Edge Width Estimation for Defocus Map from a Single Image

  • Andrey Nasonov
  • Alexandra Nasonova
  • Andrey KrylovEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9386)

Abstract

The paper presents a new edge width estimation method based on Gaussian edge model and unsharp mask analysis. The proposed method is accurate and robust to noise. Its effectiveness is demonstrated by its application for the problem of defocus map estimation from a single image. Sparse defocus map is constructed using edge detection algorithm followed by the proposed edge width estimation algorithm. Then full defocus map is obtained by propagating the blur amount at edge locations to the entire image. Experimental results show the effectiveness of the proposed method in providing a reliable estimation of the defocus map.

Keywords

Edge width Image blur Defocus map Edge model 

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References

  1. 1.
    Bae, S., Durand, F.: Defocus magnification. Computer Graphics Forum 26(3), 571–579 (2007)CrossRefGoogle Scholar
  2. 2.
    Basu, M.: Gaussian-based edge-detection methods - a survey. IEEE Transactions on Systems, Man and Cybernetics, Part C 32, 252–260 (2002)CrossRefGoogle Scholar
  3. 3.
    Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Analysis and Machine Intelligence 8, 679–698 (1986)CrossRefGoogle Scholar
  4. 4.
    Elder, J.H., Zucker, S.W.: Local scale control for edge detection and blur estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence 20(7), 699–716 (1998)CrossRefGoogle Scholar
  5. 5.
    Favaro, P., Soatto, S.: A geometric approach to shape from defocus. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(3), 406–417 (2005)CrossRefGoogle Scholar
  6. 6.
    Hu, H., de Haan, G.: Low cost robust blur estimator. In: IEEE International Conference on Image Processing, pp. 617–620 (2006)Google Scholar
  7. 7.
    Hua, Z., Wei, Z., Yaowu, C.: A no-reference perceptual blur metric by using ols-rbf network. In: Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008, vol. 1, pp. 1007–1011 (2008)Google Scholar
  8. 8.
    Levin, A., Lischinski, D., Weiss, Y.: A closed-form solution to natural image matting. IEEE Transactions on Pattern Analysis and Machine Intelligence 30(2), 228–242 (2008)CrossRefGoogle Scholar
  9. 9.
    Marziliano, P., Dufaux, F., Winkler, S., Ebrahimi, T.: A no-reference perceptual blur metric. Proceedings of the International Conference on Image Processing 3, 57–60 (2002)Google Scholar
  10. 10.
    Marziliano, P., Dufaux, F., Winkler, S., Ebrahimi, T.: Perceptual blur and ringing metrics: Application to JPEG2000. Signal Processing: Image Communications 3(2), 163–172 (2004)Google Scholar
  11. 11.
    Narvekar, N.D., Karam, L.J.: A no-reference perceptural image sharpness metric based on a cumulative probability of blur detection. In: International Workshop on Quality of Multimedia Experience, QoMEx 2009 (2009)Google Scholar
  12. 12.
    Nasonova, A.A., Krylov, A.S.: Determination of image edge width by unsharp masking. Computational Mathematics and Modeling 25(1), 72–78 (2014)CrossRefGoogle Scholar
  13. 13.
    Suzuki, K., Horiba, I., Sugie, N.: Neural edge enhancer for supervised edge enhancement from noisy images. IEEE Transactions on Pattern Analysis and Machine Intelligence 25, 1582–1596 (2003)CrossRefGoogle Scholar
  14. 14.
    Tang, C., Hou, C., Song, Z.: Defocus map estimation from a single image via spectrum contrast. Optics letters 38(10), 1706–1708 (2013)CrossRefGoogle Scholar
  15. 15.
    Zhou, C., Cossairt, O., Nayar, S.: Depth from diffusion. In: 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1110–1117. IEEE (2010)Google Scholar
  16. 16.
    Zhuo, S., Sim, T.: Defocus map estimation from a single image. Pattern Recognition 44(9), 1852–1858 (2011)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Andrey Nasonov
    • 1
  • Alexandra Nasonova
    • 1
  • Andrey Krylov
    • 1
    Email author
  1. 1.Laboratory of Mathematical Methods of Image Processing, Faculty of Computational Mathematics and CyberneticsLomonosov Moscow State UniversityMoscowRussia

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