首页 | 本学科首页   官方微博 | 高级检索  
     

光学显微成像系统图像清晰度评价函数的对比
引用本文:李雪,江旻珊.光学显微成像系统图像清晰度评价函数的对比[J].光学仪器,2018,40(1):28-38.
作者姓名:李雪  江旻珊
作者单位:上海理工大学 光电信息与计算机工程学院, 上海 200093,上海理工大学 光电信息与计算机工程学院, 上海 200093
摘    要:图像清晰度评价函数是评价各类成像系统成像质量的一个关键函数,为找到合适的图像清晰度评价算法,采用MATLAB软件对16种适用于光学显微成像系统的清晰度评价函数进行仿真,定量分析了不同算法的灵敏度、单峰性、无偏性以及运算速度。实验表明:Laplacian函数具有较高的单峰性、无偏性和灵敏度;存在高斯噪声时,Brenner函数、Tenengrad函数和基于Prewitt算子的函数以及中值滤波-离散余弦函数稳定性好;而存在椒盐噪声时,Roberts函数综合性能最优。

关 键 词:清晰度评价函数  高斯噪声  椒盐噪声  Laplacian函数
收稿时间:2017/8/29 0:00:00

A comparison of sharpness functions based on microscopes
LI Xue and JIANG Minshan.A comparison of sharpness functions based on microscopes[J].Optical Instruments,2018,40(1):28-38.
Authors:LI Xue and JIANG Minshan
Affiliation:School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China and School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
Abstract:Sharpness function is the key in the imaging systems.We compared sixteen functions to determine which function is most suitable.We took into consideration that are inherent to the autofocus algorithm,such as unbiasedness,unimodality,sensitivity and time-consumption.The simulation with MATLAB has shown that the Laplacian function would be our first choice for its best performance.But in a situation with Gaussian noise,the Brenner function,the Tenengrad function,sharpness function based on Prewitt edge detection operator and median filtering and discrete cosine function perform well.In a situation with salt and pepper noise,the Roberts function has good stability.
Keywords:sharpness function  Gaussian noise  salt and pepper noise  Laplacian function
本文献已被 CNKI 等数据库收录!
点击此处可从《光学仪器》浏览原始摘要信息
点击此处可从《光学仪器》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号