Myopic deconvolution of adaptive optics images by use of object and point-spread function power spectra
Applied Optics, Vol. 37, Issue 21, pp. 4614-4622 (1998)
http://dx.doi.org/10.1364/AO.37.004614
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Abstract
Adaptive optics systems provide a real-time compensation for atmospheric turbulence. However, the correction is often only partial, and a deconvolution is required for reaching the diffraction limit. The need for a regularized deconvolution is discussed, and such a deconvolution technique is presented. This technique incorporates a positivity constraint and some a priori knowledge of the object (an estimate of its local mean and a model for its power spectral density). This method is then extended to the case of an unknown point-spread function, still taking advantage of similar a priori information on the point-spread function. Deconvolution results are presented for both simulated and experimental data.
© 1998 Optical Society of America
[Optical Society of America ]
OCIS Codes
(010.1080) Atmospheric and oceanic optics : Active or adaptive optics
(010.1330) Atmospheric and oceanic optics : Atmospheric turbulence
(100.1830) Image processing : Deconvolution
(100.3020) Image processing : Image reconstruction-restoration
(100.3190) Image processing : Inverse problems
(110.6770) Imaging systems : Telescopes
Citation
Jean-Marc Conan, Laurent M. Mugnier, Thierry Fusco, Vincent Michau, and Gérard Rousset, "Myopic deconvolution of adaptive optics images by use of object and point-spread function power spectra," Appl. Opt. 37, 4614-4622 (1998)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-37-21-4614
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