Myopic deconvolution from wave-front sensing

Deconvolution from wave-front sensing is a powerful and low-cost high-resol ution imaging technique designed to compensate for the image degradation du e to atmospheric turbulence. It is based on a simultaneous recording of sho rt-exposure images and wave-front sensor (WFS) data. Conventional data proc essing consists of a sequential estimation of the wave fronts given the WFS data and then of the object given the reconstructed wave fronts and the im ages. However, the object estimation does not take into account the wave-fr ont reconstruction errors. A joint estimation of the object and the respect ive wave fronts has therefore been proposed to overcome this limitation. Th e aim of our study is to derive and validate a robust joint estimation appr oach, called myopic deconvolution from wave-front sensing. Our estimator us es all data simultaneously in a coherent Bayesian framework. It takes into account the noise in the images and in the WFS measurements and the availab le a priori information on the object to be restored as well as on the wave fronts. Regarding the a priori information on the object, an edge-preservi ng prior is implemented and validated. This method is validated on simulati ons and on experimental astronomical data. (C) 2001 Optical Society of Amer ica.