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Compact Lens-less Digital Holographic Microscope for MEMS Inspection and Characterization

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Windowed Fourier-filtered and quality-guided phase-unwrapping algorithm.

Qian Kemao¹, Wenjing Gao, Haixia Wang

¹School of Computer Engineering, Nanyang Technological University, Singapore. mkmqian@ntu.edu.sg

|October 11, 2008

Summary

This study introduces an improved phase-unwrapping algorithm using windowed Fourier filtering and quality guidance. The enhanced method offers greater tolerance to noisy data and adaptability for various phase-unwrapping challenges.

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Area of Science:

Optics and Photonics
Image Processing
Signal Processing

Background:

Phase unwrapping is crucial for reconstructing continuous phase from wrapped phase data.
Previous windowed Fourier transform (WFT) methods faced limitations in handling low-quality regions and adaptability.
Existing algorithms often struggle with noise and preserving fine details in phase maps.

Purpose of the Study:

To develop an advanced phase-unwrapping algorithm with improved robustness and adaptability.
To enhance tolerance to low-quality phase data and automate the unwrapping process.
To introduce adaptive window size selection for diverse phase-unwrapping applications.

Main Methods:

A novel windowed Fourier-filtered and quality-guided phase-unwrapping algorithm is proposed.
Filtered amplitude is utilized as a real-valued quality map for enhanced robustness.
Adaptive window size selection is incorporated to manage noise and preserve features.

Main Results:

The algorithm successfully unwrapped all eight test cases from Ghiglia and Pritt's benchmark dataset.
The use of a real-valued quality map significantly improves tolerance to low-quality phase regions.
Adaptive window size selection demonstrated effectiveness in noise reduction and feature preservation.

Conclusions:

The proposed algorithm represents a significant advancement in phase-unwrapping techniques.
It offers superior performance in handling noisy and complex phase data compared to previous methods.
The algorithm's adaptability makes it suitable for a wide range of scientific and engineering applications.