Filters with Noise/Phase Jump Detection Scheme for Image Reconstruction

Conference paper
Part of the Conference Proceedings of the Society for Experimental Mechanics Series book series (CPSEMS)

Abstract

Residual noise, speckle noise, and noise at the lateral surface of height discontinuities influence the image reconstruction in the wrapped phase map of a 3D object containing the height discontinuities. This paper develops two robust filters, namely Filters A and B, in order to resolve these noise problems. A previously proposed noise/phase jump detection scheme bases on the two filters. Filter A is composed of the detection scheme and an adaptive median filter, whereas Filter B replaces detected noise with the median phase value of an N × N mask centered on the noise. Three types of noise are mostly removed by Filter A, and then the remaining noise, especially the noise at the lateral surface, is removed by Filter B. The integration of two filtering algorithms and phase unwrapping algorithms is proposed for 3D image reconstruction. Two different types of phase unwrapping algorithms are used, namely the path-dependent MACY algorithm and the pathindependent cellular automata (CA) algorithm. Note that because Filters A and B remove noise precisely and clearly, they enable the phase unwrapping algorithms (e.g., MACY or CA) to successfully cross the unwrapping path of height discontinuities and easily obtain the successful 3D image reconstructions.

Keywords

Speckle noise Noise in phase map Height discontinuity Phase unwrapping 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Yamaki, R. and Hirose, A., “Singularity-Spreading Phase Unwrapping,” IEEE Transactions on Geoscience and Remote Sensing, 45(10) 3240 –3251(2007)Google Scholar
  2. 2.
    Pouet, B.F. and Krishnaswamy, S., “Technique for the removal of speckle phase in electronic speckle interferometry,” Opt. Lett. 20 (3) 318-320 (1995)CrossRefGoogle Scholar
  3. 3.
    Aebischery, H.A. and Waldner, S., “A simple and effective method for filtering speckle-interferometric phase fringe patterns,” Optics Communications 162(4-6) 205-210(1999).Google Scholar
  4. 4.
    Saldner, H.O. and Huntley, J.M., “Temporal phase unwrapping: Application to surface profiling of discontinuous objects,” Appl. Opt. 36 (13),1 2770-2775 (1997).CrossRefGoogle Scholar
  5. 5.
    William, W. and MACY, J.R., “Two-dimensional fringe-pattern analysis,” Applied Optics 22(23), 3898-3901 (1983).Google Scholar
  6. 6.
    Ghiglia, D.C., Mastin, G., and Romero, L.A., “Cellular-automata method for phase unwrapping,” J. Opt. Soc. Am. 4, 267-80 (1987).CrossRefGoogle Scholar
  7. 7.
    Spik, A. and Robinson, D.W., “Investigation of the cellular automata method for phase unwrapping and its implementation on an array processor,” Optics and Lasers in Engineering 14, 25-37 (1991).CrossRefGoogle Scholar
  8. 8.
    Chang, H.Y., Chen, C.W., Lee, C.K., and Hu, C.P., “The Tapestry Cellular Automata phase unwrapping algorithm for interferogram analysis,” Optics and Lasers in Engineering 30, 487-502 (1998).CrossRefGoogle Scholar
  9. 9.
    Weng, J.F. and Lo, Y.L., “Robust detection scheme on noise and phase jump for phase maps of objects with height discontinuities-theory and experiment,” Optics Express 19 (4), 3086-3105 (2011).CrossRefGoogle Scholar
  10. 10.
    Capanni, A., Pezzati, L., Bertani, D., Cetica, M., and Francini, F., “Phase-shifting speckle interferometry: a noise reduction filter for phase unwrapping,” Opt. Eng. 36(9), 2466–2472 (1997).CrossRefGoogle Scholar

Copyright information

© Springer Science+Businees Media, LLC 2011

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringNational Cheng Kung UniversityTainanTaiwan

Personalised recommendations