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题名:
Restoration of turbulence-degraded extended object using the stochastic parallel gradient descent algorithm: Numerical simulation
作者: Yang Huizhen; Li Xinyang; Gong Chenglong; Jiang Wenhan
刊名: Optics Express
出版日期: 2009
卷号: 17, 期号:5, 页码:3052-3062
通讯作者: Yang Huizhen
文章类型: 期刊论文
中文摘要: 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.
英文摘要: 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.
收录类别: SCI ; Ei
语种: 英语
内容类型: 期刊论文
URI标识: http://ir.ioe.ac.cn/handle/181551/6125
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作者单位: 中国科学院光电技术研究所

Recommended Citation:
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.
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