MYOPIC DECONVOLUTION OF ADAPTIVE OPTICS IMAGES BY USE OF OBJECT AND POINT-SPREAD FUNCTION POWER SPECTRA

Adaptive optics systems provide a real-time compensation for atmospher ic turbulence. However, the correction is often only partial, and a de convolution is required for reaching the diffraction limit. The need f or a regularized deconvolution is discussed, and such a deconvolution technique is presented. This technique incorporates a positivity const raint and some a priori knowledge of the object (an estimate of its lo cal mean and a model for its power spectral density). This method is t hen extended to the case of an unknown point-spread function, still ta king advantage of similar a priori information on the point-spread fun ction. Deconvolution results are presented for both simulated and expe rimental data. (C) 1998 Optical Society of America.