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首页> 外文期刊>Оптика и спектроскопия >MODULATION TRANSFER FUNCTION ESTIMATION OF OPTICAL LENS SYSTEM BY ADAPTIVE NEURO-FUZZY METHODOLOGY
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MODULATION TRANSFER FUNCTION ESTIMATION OF OPTICAL LENS SYSTEM BY ADAPTIVE NEURO-FUZZY METHODOLOGY

机译:自适应神经模糊方法估计光学透镜系统的调制传递函数

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摘要

The quantitative assessment of image quality is an important consideration in any type of imaging system. The modulation transfer function (MTF) is a graphical description of the sharpness and contrast of an imaging system or of its individual components. The MTF is also known and spatial frequency response. The MTF curve has different meanings according to the corresponding frequency. The MTF of an optical system specifies the contrast transmitted by the system as a function of image size, and is determined by the inherent optical properties of the system. In this study, the adaptive neuro-fuzzy (ANFIS) estimator is designed and adapted to estimate MTF value of the actual optical system. Neural network in ANFIS adjusts parameters of membership function in the fuzzy logic of the fuzzy inference system. The back propagation learning algorithm is used for training this network. This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated. The simulation results presented in this paper show the effectiveness of the developed method.
机译:在任何类型的成像系统中,图像质量的定量评估都是重要的考虑因素。调制传递函数(MTF)是成像系统或其各个组件的清晰度和对比度的图形描述。 MTF和空间频率响应也是已知的。根据相应的频率,MTF曲线具有不同的含义。光学系统的MTF将系统传输的对比度指定为图像大小的函数,并由系统的固有光学特性确定。在这项研究中,自适应神经模糊(ANFIS)估计器被设计并调整为估计实际光学系统的MTF值。 ANFIS中的神经网络在模糊推理系统的模糊逻辑中调整隶属函数的参数。反向传播学习算法用于训练该网络。该智能估计器是使用Matlab / Simulink实现的,并对性能进行了研究。本文给出的仿真结果证明了该方法的有效性。

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