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Efficient fringe image enhancement based on dual-tree complex wavelet transform.
Tai-Chiu Hsung1, Daniel Pak-Kong Lun, William W L Ng
1Centre for Signal Processing, Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China.
Applied Optics
|July 21, 2011
Summary
This study introduces a novel image enhancement algorithm using the oriented two-dimensional dual-tree complex wavelet transform (DT-CWT) to denoise fringe images for optical phase shift profilometry (PSP). The method significantly improves the signal-to-noise ratio (SNR) for more accurate 3D modeling.
Area of Science:
- Optics and Photonics
- Image Processing
- Computer Vision
Background:
- Optical Phase Shift Profilometry (PSP) enables real-time 3D modeling via fringe pattern projection and image capture.
- Image noise in real-world PSP applications degrades the quality of reconstructed 3D models.
Purpose of the Study:
- To develop a new image enhancement algorithm for denoising fringe images in optical PSP.
- To improve the accuracy of 3D model reconstruction from noisy fringe data.
Main Methods:
- Utilized the oriented two-dimensional dual-tree complex wavelet transform (DT-CWT) for sparse representation of fringe images.
- Implemented a novel iterative regularization procedure with an enhanced initial guess for image denoising.
- Applied the algorithm to enhance fringe images captured during optical PSP.
Main Results:
- The proposed DT-CWT based algorithm achieved an average signal-to-noise ratio (SNR) improvement of 7.2 dB over traditional methods.
- 3D model reconstruction accuracy improved by 6 to 20 dB in SNR when using the enhanced fringe images.
Conclusions:
- The novel DT-CWT based enhancement algorithm effectively denoises fringe images in optical PSP.
- This method significantly boosts the accuracy of 3D reconstruction, especially in the presence of image noise.
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