Constrained least-squares estimation in deconvolution from wave-front sensing

摘要: Abstract We address the optimal processing of astronomical images using deconvolution from wave-front sensing technique (DWFS). A constrained least-squares (CLS) solution which incorporates ensemble average DWFS data is derived Lagrange minimization. The new estimator requires data, noise statistics, OTF and a constraint. constraint can be chosen such that algorithm selects conventional regularization constant automatically. No ad hoc parameter tuning necessary. uses an iterative Newton-Raphson minimization to determine multiplier. Computer simulation 1 m telescope imaging through atmospheric turbulence used test estimation scheme. CLS object estimates are compared with those processed via manual constant. provides comparable resolution computationally inexpensive, converging in less than 10 iterations.