Ms. Congcong Yu Profile

Congcong Yu

at Xi'an Institute of Optics and Precision Mechanics CAS

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Publications (3)

Proceedings Article | 18 December 2019 Paper

Joint optimization of apodizer and lyot stop for coronagraph with four-quadrant phase mask

Rui Ge, Hui Zhao, Chuang Li, Xue-wu Fan, Cong-cong Yu

Proceedings Volume 11341, 1134102 (2019) https://doi.org/10.1117/12.2538039

KEYWORDS: Coronagraphy, Stars, Imaging systems, Chlorine, Planets, Optimization (mathematics), Telescopes, Diffraction, Sensors, Optical components

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Proceedings Article | 14 August 2019 Paper

High-resolution imaging of space target based on compressed sensing

Congcong Yu, Hui Zhao, Ling Zhang, Jing Wang, Rui Ge, Xuewu Fan

Proceedings Volume 11179, 111793U (2019) https://doi.org/10.1117/12.2539647

KEYWORDS: Computational imaging, Reconstruction algorithms, Compressed sensing, Detection and tracking algorithms, Super resolution, Image quality, Image resolution, Image restoration, Image processing, Associative arrays

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Proceedings Article | 29 July 2019 Paper

Improved vector extrapolation based Richardson-Lucy algorithm used for wavefront coded imaging and experimental demonstration

Hui Zhao, Jingjing Xia, Ling Zhang, Congcong Yu, Xuewu Fan

Proceedings Volume 11062, 110621B (2019) https://doi.org/10.1117/12.2525721

KEYWORDS: Expectation maximization algorithms, Point spread functions, Image restoration, Imaging systems, Visualization, Modulation transfer functions, Image quality, Image analysis, Signal to noise ratio, Diffraction

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Wave-front coding is a mile-stone technique that can be used to greatly extend the DOF (depth of field) of incoherent imaging system. Besides the phase mask design, the digital restoration is very crucial to obtain clear image with largely extended DOF. Richardson-Lucy (RL) algorithm is a kind of nonlinear image restoration method which is based on Poisson noise model and maximum likelihood estimation. Because RL algorithm can generate high quality restoration result and own the capability to realize super-resolution construction, it has been widely applied in the field of astronomy, macroscopic imaging and et.al. However, classical RL algorithm converges very slowly and have to be run many times to achieve an acceptable restoration result when it is applied to wave-front coded imaging system whose point spread function has quite a large support region. Our previously published results demonstrate that at least 60 times iterations are needed for each color channel, which severely prohibits real-time implementation of classical RL algorithm.. Therefore in this manuscript, an improved vector extrapolation based RL algorithm is designed by embedding the modified exponent into the framework of traditional vector extrapolation based RL algorithm. Not only a bigger iteration step indicating a bigger acceleration ratio is obtained, but also the noise amplification is effectively prohibited. Experimental results demonstrate that with the same number of iterations, the restored image corresponding to the improved vector extrapolation based RL algorithm has a better visual quality. At the same time, the structural similarity index (SSIM) is used as a criterion to determine the optimum iterations for each color channel and optimum combinations of algorithm parameters, based on which total iterations for color images are reduced approxiamately 78.9% and visually satisfactory restoration results can be obtained without denoising the restored image further. It could be considered that the work reported in this manuscript paves the way for realization of the embedded processing based real-time wave-front coded imaging in the future.

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