Open Access
MATEC Web Conf.
Volume 217, 2018
2018 International Conference on Vibration, Sound and System Dynamics (ICVSSD 2018)
Article Number 01002
Number of page(s) 7
Section Vibration
Published online 17 October 2018
  1. P. Castellini, M. Martarelli, and E. Tomasini, “Laser Doppler Vibrometry: Development of advanced solutions answering to technology’s needs,” Mechanical Systems and Signal Processing, Vol. 20, No. 6, pp. 1265–1285, 2006. [CrossRef] [Google Scholar]
  2. A. Davis, K. L. Bouman, J. G. Chen et al., “Visual vibrometry: Estimating material properties from small motions in video.” pp. 5335–5343. [Google Scholar]
  3. A. Davis, M. Rubinstein, N. Wadhwa et al., “The visual microphone: passive recovery of sound from video,” 2014. [Google Scholar]
  4. D. A. Ehrhardt, M. S. Allen, S. Yang et al., “Full-field linear and nonlinear measurements using continuous-scan laser doppler vibrometry and high speed three-dimensional digital image correlation,” Mechanical Systems and Signal Processing, Vol. 86, pp. 82–97, 2017. [CrossRef] [Google Scholar]
  5. E. P. Simoncelli, and W. T. Freeman, “The steerable pyramid: A flexible architecture for multi-scale derivative computation.” pp. 444–447. [Google Scholar]
  6. B. D. Lucas, and T. Kanade, “An iterative image registration technique with an application to stereo vision,” 1981. [Google Scholar]
  7. B. K. Horn, and B. G. Schunck, “Determining optical flow,” Artificial intelligence, Vol. 17, no. 1-3, pp. 185–203, 1981. [CrossRef] [Google Scholar]
  8. S. Mallat, A wavelet tour of signal processing: Academic press, 1999. [Google Scholar]
  9. Y. Yu, and J. Wang, “Highly Accurate Estimation of Sub-pixel Motion Using Phase Correlation.” pp. 186–193. [Google Scholar]
  10. N. Wadhwa, M. Rubinstein, F. Durand et al., “Phase-based video motion processing,” ACM Transactions on Graphics (TOG), Vol. 32, No. 4, pp. 80, 2013. [CrossRef] [Google Scholar]
  11. I. W. Selesnick, R. G. Baraniuk, and N. C. Kingsbury, “The dual-tree complex wavelet transform,” IEEE signal processing magazine, Vol. 22, No. 6, pp. 123–151, 2005. [CrossRef] [Google Scholar]
  12. R. Anderson, N. Kingsbury, and J. Fauqueur, “Determining multiscale image feature angles from complex wavelet phases.” pp. 490–498. [Google Scholar]
  13. T. Gautama, and M. Van Hulle, “A phase-based approach to the estimation of the optical flow field using spatial filtering,” IEEE Transactions on Neural Networks, Vol. 13, No. 5, pp. 1127–1136, 2002. [CrossRef] [Google Scholar]
  14. H. K. Sevindir, and C. Yazıcı, “Comparison of Wavelet and Shearlet Transforms for Medical Images,” Appl. Math, Vol. 10, No. 4, pp. 1447–1452, 2016. [Google Scholar]
  15. G. Kutyniok, and D. Labate, “Introduction to shearlets,” Shearlets, pp. 1–38: Springer, 2012. [Google Scholar]
  16. D. Scharstein, H. Hirschmüller, Y. Kitajima et al., “High-resolution stereo datasets with subpixel-accurate ground truth.” pp. 31–42. [Google Scholar]

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