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一种用于通过点源图像的软件分析来补偿初级像差的无波前传感器自适应光学系统。1. 方法。

No wavefront sensor adaptive optics system for compensation of primary aberrations by software analysis of a point source image. 1. Methods.

作者信息

Grisan Enrico, Frassetto Fabio, Da Deppo Vania, Naletto Giampiero, Ruggeri Alfredo

机构信息

Department of Information Engineering, University of Padova, Via Gradenigo 6/b, I-35131 Padova, Italy.

出版信息

Appl Opt. 2007 Sep 1;46(25):6434-41. doi: 10.1364/ao.46.006434.

Abstract

Adaptive optics (AO) has been recently used for the development of ophthalmic devices. Its main objective has been to obtain high-resolution images for diagnostic purposes or to estimate high-order eye aberrations. The core of every AO system is an optical device that is able to modify the wavefront shape of the light entering the system; if you know the shape of the incoming wavefront, it is possible to correct the aberrations introduced in the optical path from the source to the image. The aim of this paper is to demonstrate the feasibility, although in a simulated system, of estimating and correcting an aberrated wavefront shape by means of an iterative gradient-descent-like software procedure, acting on a point source image, without expensive wavefront sensors or the burdensome computation of the point-spread-function (PSF) of the optical system. In such a way, it is possible to obtain a speed and repeatability advantage over classical stochastic algorithms. A hierarchy in the aberrations is introduced, in order to reduce the dimensionality of the state space to be searched. The proposed algorithm is tested on a simple optical system that has been simulated with ray-tracing software, with randomly generated aberrations, and compared with a recently proposed algorithm for wavefront sensorless adaptive optics.

摘要

自适应光学(AO)最近已被用于眼科设备的开发。其主要目标是获取高分辨率图像用于诊断目的或估计高阶眼像差。每个AO系统的核心是一个能够改变进入系统的光的波前形状的光学装置;如果你知道入射波前的形状,就有可能校正从光源到图像的光路中引入的像差。本文的目的是证明,尽管是在模拟系统中,但通过一种类似梯度下降的迭代软件程序,作用于点源图像,在没有昂贵的波前传感器或光学系统点扩散函数(PSF)的繁重计算的情况下,估计和校正像差波前形状的可行性。通过这种方式,可以获得比传统随机算法更快的速度和更高的重复性优势。引入了像差层次结构,以降低要搜索的状态空间的维度。所提出的算法在一个用光线追踪软件模拟的、具有随机生成像差的简单光学系统上进行了测试,并与最近提出的一种无波前传感器自适应光学算法进行了比较。

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