入瞳直径8mm、视场范围30°、焦距40mm、100lp/mm时MTF>0.5。 包含初始结构以及两种优化结果（1和2）.

光学实验 双高斯物镜优化设计 ZEMAX

针对狼群算法求解复杂函数时容易陷入局部极值、计算耗费大、学习能力差等局限性, 提出一种狼群智能算法. 首先, 通过构建智能猎杀行为提高算法自适应学习能力, 降低算法的计算耗费, 构建双高斯函数更新法以增强算法全局搜索能力; 然后, 运用马尔科夫过程证明狼群智能算法的收敛性; 最后, 对多种典型测试函数进行仿真实验并与多种智能算法进行对比分析. 实验结果表明, 所提出算法具有全局收敛性强、计算耗费低、寻优精度高等优势.

zemax 光学设计系统入门的最佳选择 资源整理不易，请珍惜，零基础入门到精通光学设计是针对某一个明确或不明确的光学需求，通过光学设计师与客户的沟通、讨论与相互妥协，最终达成共识，形成满足需求的可量化可测量的光学指标，然后据此开展包括光学透镜、结构、尺寸、重量、价格、工期、工艺、材料、强度、温度等等因素在内设计工作，最终形成满足要求的光学系统

针对线激光测量系统对金属表面进行测量时强反射光影响光条提取的问题,提出了一种基于双高斯拟合的光条提取算法。首先对光条截面的灰度进行分析,发现了光条灰度的多峰分布规律;然后推导光的反射模型,对金属表面强反射光的产生原理和能量分布模型进行研究;之后根据分布模型建立双高斯拟合模型,设计光条提取算法,并用样例验证了算法的可行性;最后进行对比实验,分析了双高斯拟合法与传统光条提取算法的提取效果,并对结果进行了置信度评价。结果表明:双高斯拟合法可以有效抑制光条图像中强反射光的影响,准确提取光条中心;双高斯拟合法的置信度评价优于传统算法。

光学镜头设计

% This folder contains a collection of "fitting" functions. % (Some has demo options - the third section) % The GENERAL input to the functions should be samples of the distribution. % % for example, if we are to fit a normal distribution ('gaussian') with a mean "u" and varaince "sig"^2 % then the samples will distribute like: % samples = randn(1,10000)*sig + u % %fitting with Least-Squares is done on the histogram of the samples. % fitting with Maximum likelihood is done directly on the samples. % % % Contents of this folder % ======================= % 1) Maximum likelihood estimators % 2) Least squares estimators % 3) EM algorithm for estimation of multivariant gaussian distribution (mixed gaussians) % 4) added folders: Create - which create samples for the EM algorithm test % Plot - used to plot each of the distributions (parametric plot) % % % % % % Maximum likelihood estimators % ============================= % fit_ML_maxwell - fit maxwellian distribution % fit_ML_rayleigh - fit rayleigh distribution % (which is for example: sqrt(abs(randn)^2+abs(randn)^2)) % fit_ML_laplace - fit laplace distribution % fit_ML_log_normal- fit log-normal distribution % fit_ML_normal - fit normal (gaussian) distribution % % NOTE: all estimators are efficient estimators. for this reason, the distribution % might be written in a different way, for example, the "Rayleigh" distribution % is given with a parameter "s" and not "s^2". % % % least squares estimators % ========================= % fit_maxwell_pdf - fits a given curve of a maxwellian distribution % fit_rayleigh_pdf - fits a given curve of a rayleigh distribution % % NOTE: these fit function are used on a histogram output which is like a sampled % distribution function. the given curve MUST be normalized, since the estimator % is trying to fit a normalized distribution function. % % % % % Multivariant Gaussian distribution % ================================== % for demo of 1