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| 光学显微成像系统图像清晰度评价函数的对比 |
| A comparison of sharpness functions based on microscopes |
| 投稿时间：2017-08-29 |
| DOI：10.3969/j.issn.1005-5630.2018.01.006 |
| 中文关键词: 清晰度评价函数 高斯噪声 椒盐噪声 Laplacian函数 |
| 英文关键词:sharpness function Gaussian noise salt and pepper noise Laplacian function |
| 基金项目: |
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| 中文摘要: |
| 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。 |
| 英文摘要: |
| 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. |
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