A phase model for point spread function estimation in ground-based astronomy

In ground-based astronomy, images of objects in outer space are acquired via ground-based tele- scopes. However, the imaging system is generally interfered by atmospheric turbulence and hence images so acquired are blurred with unknown point spread function （PSF）. To restore the observed images, aberration of the wavefront at the telescope＇s aperture, i.e., the phase, is utilized to derive the PSF. However, the phase is not readily available. Instead, its gradients can be collected by wavefront sensors. Thus the usual approach is to use regularization methods to reconstruct high-resolution phase gradients and then use them to recover the phase in high accuracy. Here, we develop a model that reconstructs the phase directly. The proposed model uses the tight frame regularization and it can be solved efficiently by the Douglas-Rachford alternating direction method of multipliers whose convergence has been well established. Numerical results illustrate that our new model is efficient and gives more accurate estimation for the PSF.

In ground-based astronomy,images of objects in outer space are acquired via ground-based telescopes.However,the imaging system is generally interfered by atmospheric turbulence and hence images so acquired are blurred with unknown point spread function(PSF).To restore the observed images,aberration of the wavefront at the telescope’s aperture,i.e.,the phase,is utilized to derive the PSF.However,the phase is not readily available.Instead,its gradients can be collected by wavefront sensors.Thus the usual approach is to use regularization methods to reconstruct high-resolution phase gradients and then use them to recover the phase in high accuracy.Here,we develop a model that reconstructs the phase directly.The proposed model uses the tight frame regularization and it can be solved efciently by the Douglas-Rachford alternating direction method of multipliers whose convergence has been well established.Numerical results illustrate that our new model is efcient and gives more accurate estimation for the PSF.