In this paper, automatic filtering for amplitude and phase reconstruction in off-axis digital holography is developed. A user-friendly interface for automatic filtering is given via program design with MATLAB. The hologram to be processed is input at the front end, and automatic spectrum filtering in Fourier spectrum domain of digital holograms is realized by using clustering algorithm at the back end. The amplitude and phase images are reconstructed from the intercepted spatial-frequency spectrum by using the reconstruction algorithm. This automatic filtering program has high robustness, which can achieve reconstruction imaging for off-axis holograms correctly and effectively in the case of different off-axis angles or different image sizes. For the user interface, upon inputting an off-axis digital hologram and confirming the operation, the reconstructed amplitude and phase images can be quickly output. This user interface has the advantages of simple operation, adjustable parameters and clear feedback. Since K-means clustering is used, this filtering algorithm increases the efficiency in processing experimental data and the reliability of reconstruction imaging. The digital hologram computer-generated is used to simulate filtering processing. The results show that the quality of reconstructed images by using the presented automatic filtering is not inferior to that by conventional manual filtering.
KEYWORDS: Digital holography, Holograms, Image resolution, 3D image reconstruction, Super resolution, Digital imaging, Holography, Reconstruction algorithms, Spatial resolution, Charge-coupled devices
In this paper, an off-axis digital holography multi-frame image super-resolution reconstruction method is presented. Each low-resolution hologram will have small displacement in different directions. The obtained low-resolution holograms are processed iteratively with the super-resolution algorithm to obtain the super-resolution hologram, and then the amplitude image is reconstructed from the super-resolution hologram. The imaging results show that the resolution of the reconstructed image after super-resolution processing is obviously improved, because of increase of high-frequency information in the high-resolution hologram.
A noise reduction method based on a shorter synthetic-wavelength in DWDH is proposed in this paper. The unwrapped phase at longer synthetic-wavelength is calculated by using the wrapped phases of two individual wavelengths. By comparing the amplified phase of longer synthetic wavelength, of which magnification is equal to that of wavelengths with the wrapped phase of a single wavelength, the difference of phase noises between the longer synthetic-wavelength phase map and the single-wavelength phase map can be calculated, and then accurate height at single-wavelength can be achieved. The proposed method for calculating phase noise is performed by comparing the phases between the single-wavelength with the shorter synthetic wavelength, and then the height at shorter synthetic-wavelength can be obtained. Compared with the existing method, the proposed method can reduce certain noise and benefit the phase reconstruction of fine structures.
The optimization of image resolution for digital holographic scanning imaging of biological cells is investigated. Digital holographic scanning imaging experiments on the upper epidermal cells of onions are performed to demonstrate the validity of resolution optimization algorithm. In the experiments, the holograms of the upper epidermal cells of onion are recorded at a certain scanning rate, and then are processed by using the resolution optimization algorithm. As a result, the phase images of the onion epidermal cells with higher contrast and resolution are obtained. According to the synthetic holograms, the changes of cell nucleus and actin microfilament inside onion’s epidermal cells are displayed. In addition, the dehydration process and plasmolysis phenomenon inside onion epidermal cells are also exhibited by recording longterm scanning holograms of living epidermal cells. The experimental results demonstrate that image quality of living onion epidermal cells can be improved by optimizing the algorithms.
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