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Digital Holographic Microscopy (DHM) enables the three-dimensional (3D) reconstruction of quantitative phase distributions from a defocused hologram. We have developed a synergistic computational framework to simultaneously compensate for the linear tilt introduced in off-axis DHM systems and focus the defocused holograms by minimizing a cost function, providing in-focus reconstructed phase images without phase distortions.
Digital Holographic Microscopy (DHM) enables the three-dimensional (3D) reconstruction of quantitative phase distributions from a defocused hologram. We have developed a synergistic computational framework to simultaneously compensate for the linear tilt introduced in off-axis DHM systems and focus the defocused holograms by minimizing a cost function, providing in-focus reconstructed phase images without phase distortions.
3D QPI-DHM
The proposed framework is based on the minimization of a synergetic cost function (SCF) that has been specifically designed for phase imaging based on: (1) the normalized variance (NV) value of in-focus reconstructed amplitude images for pure phase objects is minimum, and (2) the best reconstructed phase image should have the least number of phase discontinuities (i.e., minimum TSM value).
The proposed framework is based on the minimization of a synergetic cost function (SCF) that has been specifically designed for phase imaging based on: (1) the normalized variance (NV) value of in-focus reconstructed amplitude images for pure phase objects is minimum, and (2) the best reconstructed phase image should have the least number of phase discontinuities (i.e., minimum TSM value).
3D QPI-DHM
The block diagram contains four stages. The first stage is focused on defining the input parameters, which are the defocused hologram (h), the source wavelength (λ), and the pixel size (Δxy). The second one corresponds to the spatial filtering of the hologram spectrum (H) to select the object frequencies. The third and fourth steps are focused on the generation of the SCF function, its minimization, and the corresponding reconstruction of in-focus reconstructed phase images with minimum phase distortions.
The block diagram contains four stages. The first stage is focused on defining the input parameters, which are the defocused hologram (h), the source wavelength (λ), and the pixel size (Δxy). The second one corresponds to the spatial filtering of the hologram spectrum (H) to select the object frequencies. The third and fourth steps are focused on the generation of the SCF function, its minimization, and the corresponding reconstruction of in-focus reconstructed phase images with minimum phase distortions.
Methods of use
Methods of use
We have developed CPU and GPU implementations for the 3D QPI-DHM tool. Two CPU scripts were developed in MATLAB - one implements a nested-loop strategy to find the target variables, and the other one implements an heuristics algorithm. The GPU script is developed in Python CUDA.
We have developed CPU and GPU implementations for the 3D QPI-DHM tool. Two CPU scripts were developed in MATLAB - one implements a nested-loop strategy to find the target variables, and the other one implements an heuristics algorithm. The GPU script is developed in Python CUDA.
Credits
Credits
- 3D QPI-DHM was developed in Python 3.7 and Matlab R2023a. Natick, Massachusetts: The MathWorks Inc.
Citation
Citation
If using 3D QPI-DHM for publication, please kindly cite the following:
If using 3D QPI-DHM for publication, please kindly cite the following:
- R. Castaneda, C. Trujillo, and A. Doblas, "In-focus quantitative phase imaging from defocused off-axis holograms: synergistic reconstruction framework," Opt. Letters 48(23), 6244-6247 (2023). doi: 10.1364/OL.506400
Support or Contact The Principal Investigators of 3D QPI-DHM project are Dr. Carlos Trujillo and Dr. Ana Doblas.
Support or Contact The Principal Investigators of 3D QPI-DHM project are Dr. Carlos Trujillo and Dr. Ana Doblas.
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