Noise-reduction for fringe analysis using the empirical mode decomposition with the generalized analysis model

Phase-extraction from fringe patterns is an inevitable procedure in many applications, such as interferometry, moire analysis, and profilometry using structured light illumination. Errors to phase-extraction always occur when the signal-to-noise ratio is weak. In this paper, we use the empirical mode decomposition (EMD) with a generalized analysis model to reduce the white noise from a fringe pattern. It is found that phases can be extracted with high accuracy once noise-reduction is performed with this model.

[1]  E. Nezry,et al.  Adaptive speckle filters and scene heterogeneity , 1990 .

[2]  J. Lim Image restoration by short space spectral subtraction , 1980 .

[3]  R. Muller,et al.  Stroboscopic interferometer system for dynamic MEMS characterization , 2000, Journal of Microelectromechanical Systems.

[4]  L. Deck,et al.  High-speed noncontact profiler based on scanning white-light interferometry. , 1994, Applied optics.

[5]  V. Srinivasan,et al.  Automated phase-measuring profilometry of 3-D diffuse objects. , 1984, Applied optics.

[6]  John R. Tyrer,et al.  Manipulation of the Fourier Components of Speckle Fringe Patterns as Part of an Interferometric Analysis Process , 1989 .

[7]  Alejandro Federico,et al.  Evaluation of the 1D empirical mode decomposition method to smooth digital speckle pattern interferometry fringes , 2007 .

[8]  K. Reichard,et al.  Calibration-based phase-shifting projected fringe profilometry for accurate absolute 3D surface profile measurement , 2003 .

[9]  E. Nezry,et al.  Structure detection and statistical adaptive speckle filtering in SAR images , 1993 .

[10]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[11]  Guillermo H. Kaufmann,et al.  An Evaluation of Synthetic Aperture Radar Noise Reduction Techniques for the Smoothing of Electronic Speckle Pattern Interferometry Fringes , 1995 .

[12]  Alexander A. Sawchuk,et al.  Adaptive restoration of images with speckle , 1987, IEEE Trans. Acoust. Speech Signal Process..

[13]  M. Takeda,et al.  Fourier transform profilometry for the automatic measurement of 3-D object shapes. , 1983, Applied optics.

[14]  G S Kino,et al.  Mirau correlation microscope. , 1990, Applied optics.

[15]  R E Brooks,et al.  Moiré gauging using optical interference patterns. , 1969, Applied optics.