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Compact Lens-less Digital Holographic Microscope for MEMS Inspection and Characterization
Published on: July 5, 2016
Millimeter-wave compressive holography
Christy Fernandez Cull1, David A Wikner, Joseph N Mait
1Fitzpatrick Institute for Photonics and Department of Electrical and Computer Engineering, Duke University, 129 Hudson Hall, Durham, North Carolina 27708, USA. caf11@ee.duke.edu
Applied Optics
|July 22, 2010
Summary
This study introduces a millimeter-wave holographic imaging system for 3D object estimation using compressive sensing. The system achieves accurate 3D reconstructions even with undersampled data, improving tomographic imaging capabilities.
Area of Science:
- Applied Physics
- Electromagnetics
- Imaging Science
Background:
- Holographic imaging offers high-resolution 3D reconstruction capabilities.
- Compressive sensing enables efficient data acquisition by reducing sampling requirements.
- Millimeter-wave frequencies provide unique penetration and resolution characteristics for object imaging.
Purpose of the Study:
- To develop and evaluate an active millimeter-wave holographic imaging system for 3D tomographic object estimation.
- To investigate the effectiveness of compressive measurements in reducing data acquisition for 3D imaging.
- To compare different reconstruction algorithms for holographic data.
Main Methods:
- Utilized a single-pixel incoherent receiver to record 2D digitized Gabor holograms.
- Implemented two compressive measurement strategies: direct 2D hologram inversion and randomly subsampled hologram inversion.
- Employed a convex quadratic minimization algorithm with total variation (TV) regularization for 3D object estimation.
Main Results:
- Achieved accurate 3D object reconstructions from both full and undersampled Gabor holograms.
- Demonstrated that TV minimization directly estimates the 3D object, unlike backpropagation which estimates the electromagnetic field.
- Maintained consistent range resolution with the 3D object's band volume despite undersampling.
Conclusions:
- The developed millimeter-wave holographic imaging system effectively performs 3D tomographic object estimation using compressive sensing.
- Total variation minimization is a robust algorithm for reconstructing 3D objects from undersampled holographic data.
- Compressive holographic imaging offers a promising approach for efficient and high-resolution 3D object reconstruction.
