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Adaptive noise reduction method for DSPI fringes based on bi-dimensional ensemble empirical mode decomposition
1State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai, China. beckham9572@163.com
Optics Express
|September 22, 2011
Summary
This study introduces a novel denoising technique for Digital Speckle Pattern Interferometry (DSPI) fringes using bi-dimensional ensemble empirical mode decomposition (BEEMD). BEEMD effectively overcomes mode mixing issues, enhancing fringe quality for accurate measurements.
Area of Science:
- Optical Metrology
- Signal Processing
- Image Analysis
Background:
- Digital Speckle Pattern Interferometry (DSPI) fringes suffer from low spatial information due to speckle noise and background intensity variations.
- Existing denoising methods, like bi-dimensional empirical mode decomposition (BEMD), face challenges with mode mixing, limiting their practical use.
- Bi-dimensional ensemble empirical mode decomposition (BEEMD), incorporating noise-assisted data analysis (NADA), addresses the mode mixing problem.
Purpose of the Study:
- To present a novel denoising approach for DSPI fringes utilizing BEEMD.
- To evaluate the effectiveness of the BEEMD-based denoising method.
- To compare the proposed method against traditional denoising techniques.
Main Methods:
- Application of bi-dimensional ensemble empirical mode decomposition (BEEMD) for noise reduction in DSPI fringes.
- Utilizing the noise-assisted data analysis (NADA) method to improve decomposition.
- Qualitative and quantitative evaluation using simulated and experimental DSPI fringe patterns.
Main Results:
- BEEMD effectively suppresses speckle noise and background intensity variations in DSPI fringes.
- The proposed method demonstrates superior performance compared to conventional denoising techniques.
- BEEMD successfully resolves the mode mixing issue inherent in BEMD.
Conclusions:
- BEEMD offers a robust and adaptive solution for denoising DSPI fringes.
- The developed technique enhances fringe quality, leading to more reliable metrological measurements.
- This method provides a significant advancement in processing noisy interferometric data.
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