Browsing by Author "Zhou, Wenjing"

Now showing 1 - 3 of 3
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    Automatic elimination of phase aberrations in digital holography based on Gaussian 1o-criterion and histogram segmentation
    Chen, Zhenkai; Zhou, Wenjing; Duan, Lian; Zhang, Hongbo; Zheng, Huadong; Xia, Xinxing; Yu, Yingjie; Poon, Ting-chung (Optica Publishing Group, 2023-04)
    We propose a numerical and automatic quadratic phase aberration elimination method in digital holography for phase-contrast imaging. A histogram segmentation method based on Gaussian 1 sigma-criterion is used to obtain the accurate coefficients of quadratic aberrations using the weighted least-squares algorithm. This method needs no manual intervention for specimen-free zone or prior parameters of optical components. We also propose a maximum-minimum-average -standard deviation (MMASD) metric to quantitatively evaluate the effectiveness of quadratic aberration elimination. Simulation and experimental results are demonstrated to verify the efficacy of our proposed method over the traditional least-squares algorithm.
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    Fast Method of Recovering Reference-Wave Intensity in Two-Step-Only Quadrature Phase-Shifting Holography
    Zhou, Wenjing; Zheng, Caifu; Poon, Ting-Chung (MDPI, 2017-10-19)
    We present a simple yet effective method, without the need for any additional recording of intensity maps or tremendous iterative computations, to recover reference-wave intensity resulting from the complex hologram acquired by quadrature phase-shifting holography. This is achieved by utilizing a certain area of interest in the complex hologram. We select a particular area in the complex hologram where there is negligible diffraction from the test sample to estimate the reference-wave intensity. The calculated intensity value allows us to extract exact phase distribution of the object in the context of two-step-only quadrature phase-shifting holography (TSO-PSH) without the zeroth-order beam and the twin image noise on the reconstruction plane. Computer simulation and experimental results have been performed to verify the effectiveness and feasibility of our proposed method.
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    Study of Image Classification Accuracy with Fourier Ptychography
    Zhang, Hongbo; Zhang, Yaping; Wang, Lin; Hu, Zhijuan; Zhou, Wenjing; Tsang, Peter W. M.; Cao, Deng; Poon, Ting-Chung (MDPI, 2021-05-14)
    In this research, the accuracy of image classification with Fourier Ptychography Microscopy (FPM) has been systematically investigated. Multiple linear regression shows a strong linear relationship between the results of image classification accuracy and image visual appearance quality based on PSNR and SSIM with multiple training datasets including MINST, Fashion MNIST, Cifar, Caltech 101, and customized training datasets. It is, therefore, feasible to predict the image classification accuracy only based on PSNR and SSIM. It is also found that the image classification accuracy of FPM reconstructed with higher resolution images is significantly different from using the lower resolution images under the lower numerical aperture (NA) condition. The difference is yet less pronounced under the higher NA condition.