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23 February 2006 3D deconvolution of adaptive-optics corrected retinal images
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We report on a deconvolution method developed in a Bayesian framework for adaptive-optics corrected images of the human retina. The method takes into account the three-dimensional nature of the imaging process; it incorporates a positivity constraint and a regularization metric in order to avoid uncontrolled noise amplification. This regularization metric is designed to simultaneously smooth noise out and preserve edges, while staying convex in order to keep the solution unique. We demonstrate the effectiveness of the method, and in particular of the edge-preserving regularization, on realistic simulated data.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
G. Chenegros, L. M. Mugnier, F. Lacombe, and M. Glanc "3D deconvolution of adaptive-optics corrected retinal images", Proc. SPIE 6090, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XIII, 60900P (23 February 2006); doi: 10.1117/12.645233;

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