Restoration of turbulence-degraded extended object using the stochastic parallel gradient descent algorithm: numerical simulation
Optics Express, Vol. 17, Issue 5, pp. 3052-3062 (2009)
http://dx.doi.org/10.1364/OE.17.003052
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Abstract
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.
© 2009 Optical Society of America
OCIS Codes
(010.0010) Atmospheric and oceanic optics : Atmospheric and oceanic optics
(010.1080) Atmospheric and oceanic optics : Active or adaptive optics
(110.0110) Imaging systems : Imaging systems
(350.4600) Other areas of optics : Optical engineering
ToC Category:
Atmospheric and Oceanic Optics
History
Original Manuscript: November 3, 2008
Revised Manuscript: January 4, 2009
Manuscript Accepted: January 21, 2009
Published: February 17, 2009
Citation
Huizhen Yang, Xinyang Li, Chenglong Gong, and Wenhan Jiang, "Restoration of turbulence-degraded extended
object using the stochastic parallel gradient
descent algorithm: numerical simulation," Opt. Express 17, 3052-3062 (2009)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-17-5-3052
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