Practical methods for automated reconstruction and characterization of particles in digital in-line holograms
Hologram reconstruction algorithms often undersample the phase in propagation kernels for typical parameters of holographic optical setups. Given in this paper is an algorithm that addresses this phase undersampling in reconstructing digital in-line holograms of particles for these typical parameters. This algorithm has a lateral sample spacing constant in reconstruction distance, has a diffraction limited resolution, and can be implemented with computational speeds comparable to the fastest of other reconstruction algorithms. This algorithm is shown to be accurate by testing with analytical solutions to the Huygens-Fresnel propagation integral. A low-pass filter can be applied to enforce a uniform minimum particle size detection limit throughout a sample volume, allowing this method to be useful in measuring particle size distributions and number densities. Tens of thousands of holograms of cloud ice particles are digitally reconstructed using the algorithm discussed. Positions of ice particles in the size range of 20 νm-1.5 mm are obtained using an algorithm that accurately finds the position of large and small particles along the optical axis. The digital reconstruction and particle characterization algorithms are implemented in an automated fashion with no user intervention on a computer cluster. Strategies for efficient algorithm implementation on a computer cluster are discussed. © 2009 IOP Publishing Ltd.
Measurement Science and Technology
Practical methods for automated reconstruction and characterization of particles in digital in-line holograms.
Measurement Science and Technology,
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