scholarly journals Fringe pattern analysis using a one-dimensional modified Morlet continuous wavelet transform

2008 ◽  
Author(s):  
Abdulbasit Z. Abid ◽  
Munther A. Gdeisat ◽  
David R. Burton ◽  
Michael J. Lalor ◽  
Hussein S. Abdul-Rahman ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Fringe Pattern ◽  
Pattern Analysis ◽  
Continuous Wavelet ◽  
One Dimensional ◽  
Morlet Continuous Wavelet Transform ◽  
Fringe Pattern Analysis

Spatial fringe pattern analysis using the two-dimensional continuous wavelet transform employing a cost function

2007 ◽  
Vol 46 (24) ◽  
pp. 6120 ◽  
Author(s):  
Abdulbasit Z. Abid ◽  
Munther A. Gdeisat ◽  
David R. Burton ◽  
Michael J. Lalor ◽  
Francis Lilley
Keyword(s):  
Wavelet Transform ◽  
Cost Function ◽  
Continuous Wavelet Transform ◽  
Fringe Pattern ◽  
Pattern Analysis ◽  
Continuous Wavelet ◽  
Two Dimensional ◽  
Fringe Pattern Analysis

Spatial and temporal carrier fringe pattern demodulation using the one-dimensional continuous wavelet transform: Recent progress, challenges, and suggested developments

2009 ◽  
Vol 47 (12) ◽  
pp. 1348-1361 ◽  
Author(s):  
Munther A. Gdeisat ◽  
Abdulbasit Abid ◽  
David R. Burton ◽  
Michael J. Lalor ◽  
Francis Lilley ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Recent Progress ◽  
Fringe Pattern ◽  
Continuous Wavelet ◽  
One Dimensional ◽  
The One

Spatial carrier fringe pattern demodulation by use of a two-dimensional continuous wavelet transform

2006 ◽  
Vol 45 (34) ◽  
pp. 8722 ◽  
Author(s):  
Munther A. Gdeisat ◽  
David R. Burton ◽  
Michael J. Lalor
Keyword(s):  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Fringe Pattern ◽  
Continuous Wavelet ◽  
Two Dimensional

Two-dimensional wavelet transform for reliability-guided phase unwrapping in optical fringe pattern analysis

2012 ◽  
Vol 51 (12) ◽  
pp. 2026 ◽  
Author(s):  
Sikun Li ◽  
Xiangzhao Wang ◽  
Xianyu Su ◽  
Feng Tang
Keyword(s):  
Wavelet Transform ◽  
Fringe Pattern ◽  
Pattern Analysis ◽  
Phase Unwrapping ◽  
Two Dimensional ◽  
Fringe Pattern Analysis

Relative acoustic impedance from wavelet transform

2014 ◽  
Vol 2 (1) ◽  
pp. SA107-SA118 ◽  
Author(s):  
Marcílio Castro de Matos ◽  
Rodrigo Penna ◽  
Paulo Johann ◽  
Kurt Marfurt
Keyword(s):  
Wavelet Transform ◽  
Continuous Wavelet Transform ◽  
Seismic Data ◽  
Acoustic Impedance ◽  
Real Data ◽  
Velocity Model ◽  
Continuous Wavelet ◽  
Reconstruction Process ◽  
Seismic Wavelet ◽  
Morlet Continuous Wavelet Transform

Most deconvolution algorithms try to transform the seismic wavelet into spikes by designing inverse filters that remove an estimated seismic wavelet from seismic data. We assume that seismic trace subtle discontinuities are associated with acoustic impedance contrasts and can be characterized by wavelet transform spectral ridges, also called modulus maxima lines (WTMML), allowing us to improve seismic resolution by using the wavelet transform. Specifically, we apply the complex Morlet continuous wavelet transform (CWT) to each seismic trace and compute the WTMMLs. Then, we reconstruct the seismic trace with the inverse continuous wavelet transform from the computed WTMMLs with a broader band complex Morlet wavelet than that used in the forward CWT. Because the reconstruction process preserves amplitude and phase along different scales, or frequencies, the result looks like a deconvolution method. Considering this high-resolution seismic representation as a reflectivity approximation, we estimate the relative acoustic impedance (RAI) by filtering and trace integrating it. Conventional deconvolution algorithms assume the seismic wavelet to be stochastic, while the CWT is implicitly time varying such that it can be applied to both depth and time-domain data. Using synthetic and real seismic data, we evaluated the effectiveness of the methodology on detecting seismic events associated with acoustic impedance changes. In the real data examples, time and in-depth RAI results, show good correlation with real P-impedance band-pass data computed using more rigorous commercial inversion software packages that require well logs and low-frequency velocity model information.

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