区域方差和点锐度相结合的多聚焦图像融合

赵迪迪; 季轶群

doi:10.3788/YJYXS20193403.0278

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区域方差和点锐度相结合的多聚焦图像融合

图像处理 | 更新时间：2020-07-05

- 区域方差和点锐度相结合的多聚焦图像融合
- Multi-focus image fusion combining regional variance and EAV
- 液晶与显示 2019年34卷第3期页码：278-282
- 作者机构：
  
  1.苏州大学光电科学与工程学院 & 苏州纳米科技协同创新中心, 江苏苏州 215006
  2.江苏省先进光学制造技术重点实验室 & 教育部现代光学技术重点实验室, 江苏苏州 215006
- 作者简介：
  
  [ "赵迪迪(1994-), 男, 江苏苏州人, 硕士研究生, 2016年于苏州科技大学获得学士学位, 主要研究方向为光学仪器与光学设计、图像处理。E-mail:1016532033@qq.com" ]
  [ "季轶群(1980-), 女, 江苏宜兴人, 博士, 副研究员, 2009年于苏州大学获得博士学位, 主要从事光学仪器与光学设计方面的研究工作。E-mail:jiyiqun@suda.edu.cn" ]
- 基金信息：
  
  国家自然科学基金(61405134);江苏省自然科学基金(BK20130320);江苏高校优势学科建设工程资助项目;Supported by National Natural Science Foundation of China(61405134);Jiangsu Natural Science Foundation(BK20130320);Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)
- DOI：10.3788/YJYXS20193403.0278
  中图分类号： TP391.41
- 收稿日期：2018-08-12，
  
  录用日期：2018-9-24，
  
  纸质出版日期：2019-03
- 稿件说明：
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赵迪迪, 季轶群. 区域方差和点锐度相结合的多聚焦图像融合[J]. 液晶与显示, 2019,34(3):278-282.

Di-di ZHAO, Yi-qun JI. Multi-focus image fusion combining regional variance and EAV[J]. Chinese journal of liquid crystals and displays, 2019, 34(3): 278-282.
赵迪迪, 季轶群. 区域方差和点锐度相结合的多聚焦图像融合[J]. 液晶与显示, 2019,34(3):278-282. DOI： 10.3788/YJYXS20193403.0278.

Di-di ZHAO, Yi-qun JI. Multi-focus image fusion combining regional variance and EAV[J]. Chinese journal of liquid crystals and displays, 2019, 34(3): 278-282. DOI： 10.3788/YJYXS20193403.0278.

摘要

针对光学成像系统景深范围有限、景深范围外目标成像模糊的问题，提出一种区域方差和点锐度相结合的拉普拉斯金字塔变换图像融合方法。该方法首先对多幅源图像做拉普拉斯金字塔变换，提取源图像在不同频率层的特征信息；对金字塔顶层图像和其余各层图像，分别采用区域方差和点锐度作为融合度量，对其进行融合，得到融合图像的金字塔各层系数；最后进行拉普拉斯金字塔逆变换得到融合图像。仿真结果表明，本文方法得到的融合图像主观视觉效果和客观评价指标均优于其他常用算法，标准差、互信息和边缘保持度分别提高了0.24%、6.8%和8.4%。该方法有效降低了融合图像的噪声，获得了更加丰富的边缘信息，对实现光学成像系统在大视场范围获取高分辨率光学图像具有重要意义。

Abstract

Depth of field of traditional optical systems is limited

it is hard to achieve a wide field image with high resolution. A novel fusion method of multi-focus image based on Laplacian pyramid transform which evaluated by the metrics of regional variance and Point sharpness (EAV) was proposed. The fusion method firstly performs Laplacian pyramid transform on multiple source images

and feature information at the layers with different frequencies were extracted. Then

the multiple source images were fused by utilizing the metric of regional variance for the top layer

and EAV for the other layers. Finally

the fused image was achieved through the inverse Laplacian pyramid transform. The obtained fused image is with lower noise and more abundant edge information than those achieved by the commonly used methods. After evaluation

the standard deviation

the mutual information and the edge retention are improved by a factor of 0.24%

6.8% and 8.4%

respectively. It is of great significance for optical systems to achieve images with high-resolution over a wide field of view.

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