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Restoration of turbulence-degraded extended object using the stochastic parallel gradient descent algorithm: Numerical simulation
Yang Huizhen; Li Xinyang; Gong Chenglong; Jiang Wenhan
Source PublicationOptics Express
Volume17Issue:5Pages:3052-3062
2009
Language英语
Indexed BySCI ; Ei
Subtype期刊论文
AbstractAn adaptive optics (AO) system with Stochastic Parallel Gradient Descent (SPGD) algorithm and a 61-element deformable mirror is simulated to restore the image of a turbulence-degraded extended object. SPGD is used to search the optimum voltages for the actuators of the deformable mirror. We try to find a convenient image performance metric, which is needed by SPGD, merely from a gray level distorted image and without any additional optics elements. Simulation results show the gray level variance function acts more promising than other metrics, such as metrics based on the gray level gradient of each pixel. The restoration capability of the AO system is investigated with different images and different turbulence strength wave-front aberrations using SPGD with the above resultant image quality criterion. Numerical simulation results verify the performance metric is effective and the AO system can restore those images degraded by different turbulence strengths successfully.; An adaptive optics (AO) system with Stochastic Parallel Gradient Descent (SPGD) algorithm and a 61-element deformable mirror is simulated to restore the image of a turbulence-degraded extended object. SPGD is used to search the optimum voltages for the actuators of the deformable mirror. We try to find a convenient image performance metric, which is needed by SPGD, merely from a gray level distorted image and without any additional optics elements. Simulation results show the gray level variance function acts more promising than other metrics, such as metrics based on the gray level gradient of each pixel. The restoration capability of the AO system is investigated with different images and different turbulence strength wave-front aberrations using SPGD with the above resultant image quality criterion. Numerical simulation results verify the performance metric is effective and the AO system can restore those images degraded by different turbulence strengths successfully.
Document Type期刊论文
Identifierhttp://ir.ioe.ac.cn/handle/181551/6125
Collection自适应光学技术研究室(八室)
Corresponding AuthorYang Huizhen
Affiliation中国科学院光电技术研究所
Recommended Citation
GB/T 7714
Yang Huizhen,Li Xinyang,Gong Chenglong,et al. Restoration of turbulence-degraded extended object using the stochastic parallel gradient descent algorithm: Numerical simulation[J]. Optics Express,2009,17(5):3052-3062.
APA Yang Huizhen,Li Xinyang,Gong Chenglong,&Jiang Wenhan.(2009).Restoration of turbulence-degraded extended object using the stochastic parallel gradient descent algorithm: Numerical simulation.Optics Express,17(5),3052-3062.
MLA Yang Huizhen,et al."Restoration of turbulence-degraded extended object using the stochastic parallel gradient descent algorithm: Numerical simulation".Optics Express 17.5(2009):3052-3062.
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