Two-dimensional windowed Fourier transform for fringe pattern analysis: Principles, applications and implementations
By Qian Kemao. 2007
729 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Mechanical Engineering, Media Technology
View Paper: https://www.semanticscholar.org/paper/7026d67acbfce61761208e782cc600cfb2b044b3
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In Computer Vision and Pattern Recognition
In Mechanical Engineering
In Media Technology
Citations in the corpus
- Quality-guided phase unwrapping technique: comparison of quality maps and guiding strategies. (2011, methodology): “For example in phase-shifting methods a complex-valued fringe pattern f c can be obtained as [32] where j is the imaginary unit, φ w is the wrapped phase, and M is the intensity modulation.”
- The Grid Method for In‐plane Displacement and Strain Measurement: A Review and Analysis (2016, methodology): “Some authors employ a Gaussian analysis window on the ground that it minimizes the Heisenberg box [108, 138].”
- Fringe projection techniques: Whither we are? (2010, methodology): “introduced in the context of fringe projection profilometry are Fourier transform method and numerous extensions of it [67, 84, 85, 86, 87, 88, 89, 90], interpolated Fourier transform [68], regressive Fourier transform [135, 69], dilating Gabor transform [70], windowed Fourier transform [71, 136], m”
- High-speed 3D shape measurement with structured light methods: A review (2018, methodology): “To alleviate the problems associated with FTP methods, Kemao [68,69] proposed Windowed Fourier Transform (WFT) method they have substantially increased the robustness [70] and broadly extended the applications [71] of FTP methods.”
- Temporal phase unwrapping algorithms for fringe projection profilometry: A comparative review (2016, methodology): “Many fringe analysis techniques have been proposed to extract the phase distribution from the distorted fringe(s), such as phase-shifting profilometry [12–15], Fouriertransform profilometry [5,7,16,17], windowed Fourier-transform profilometry [64,65] and wavelet-transform profilometry [66,67].”
- Fringe pattern analysis using deep learning (2018, neutral): “…(PS) methods that require multiple fringe patterns to extract phase information, 4 and (2) spatial phase-demodulation methods that allow phase retrieval from a single fringe pattern, such as the Fourier transform (FT), 5 windowed Fourier transform (WFT), 6 and wavelet transform (WT) methods.”