A phase model using the Huber norm for estimating point spread function under frozen flow hypothesis

摘要: Abstract In astronomical observation and space exploration, the light of an object in outer is inevitably distorted by atmospheric turbulence around Earth before it reaches ground-based telescope aperture. The target so observed degraded unknown point spread functions (PSFs). Estimating PSFs thus crucial for astronomy. order to know PSFs, we first need estimate phase, i.e., wavefront aberration incoming at this paper, under frozen flow hypothesis, propose a new model estimating phase case single- multi-layered turbulence. model, which deploys Huber norm as regularizer, can be cast saddle-point problem solved efficiently existing well-developed optimization algorithms. We test spatially-varying image deblurring using estimated demonstrates compelling numerical performance model.