Analysis and improvement on sharpness evaluation function of defocused image

HONG YU-zhen; REN Guo-qiang; SUN Jian

doi:10.3788/OPE.20142212.3401

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Analysis and improvement on sharpness evaluation function of defocused image

更新时间：2020-08-13

- Analysis and improvement on sharpness evaluation function of defocused image
- Optics and Precision Engineering Vol. 22, Issue 12, Pages: 3401-3408(2014)
- 作者机构：
  
  1. 中国科学院大学北京,中国,100049
  2. 中国科学院光电技术研究所,四川成都,610209
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20142212.3401
  CLC： TP391
- Received：04 August 2014，
  
  Revised：11 September 2014，
  
  Published：25 December 2014
- 稿件说明：
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洪裕珍, 任国强, 孙健. 离焦模糊图像清晰度评价函数的分析与改进[J]. 光学精密工程, 2014,22(12): 3401-3408

HONG YU-zhen, REN Guo-qiang, SUN Jian. Analysis and improvement on sharpness evaluation function of defocused image[J]. Editorial Office of Optics and Precision Engineering, 2014,22(12): 3401-3408
洪裕珍, 任国强, 孙健. 离焦模糊图像清晰度评价函数的分析与改进[J]. 光学精密工程, 2014,22(12): 3401-3408 DOI： 10.3788/OPE.20142212.3401.

HONG YU-zhen, REN Guo-qiang, SUN Jian. Analysis and improvement on sharpness evaluation function of defocused image[J]. Editorial Office of Optics and Precision Engineering, 2014,22(12): 3401-3408 DOI： 10.3788/OPE.20142212.3401.

摘要

传统的基于梯度的图像清晰度评价函数(调焦函数)对噪声敏感

在实际应用中易引入过多的非边缘信息

影响系统的稳定性.本文基于光学成像系统离焦模型分析了系统离焦对图像清晰度的影响

并提出了一种改进的图像清晰度评价方法.该方法利用最大灰度差提取细节信息来评价图像清晰度;引入阈值区分边缘点和非边缘点来减小图像平坦区域对评价函数灵敏度的影响

同时有效抑制噪声的干扰.进行了仿真实验和实际测试并与传统的清晰度评价函数进行了比较.结果显示

提出的方法具有更好的灵敏度和抗噪性能

能够准确而稳定地评价离焦模糊图像的清晰度

可用于实际光学系统的自动调焦.

Abstract

Traditional gradient based image sharpness evaluation functions are sensitive to noise

which is easy to introduce more non-edge information and shows poor stability in practical applications. This paper analyzes the effect of the defocus of an optical imaging system on image sharpness based on the defocused model and proposes a improved sharpness evaluation method. The method uses the maximum gradient as the criterion of image sharpness.Then

it introduces the optimal threshold to distinguish the edge points and non-edge points to reduce the impact of the gradient of flat area and the noise in the image on evaluation results and to suppress the noise interference. The simulation experiments and actual test are performed and obtained results are compared with that of different traditional methods. It is verified that the improved method has better sensitivity and noise immunity

which is able to evaluate the sharpness of defocused image accurately and is suitable for auto-focusing in actual optical imaging systems.

关键词

Keywords

references

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