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基于小波域清晰度评价的光场全聚焦图像融合

谢颖贤 武迎春 王玉梅 赵贤凌 王安红

谢颖贤, 武迎春, 王玉梅, 等 . 基于小波域清晰度评价的光场全聚焦图像融合[J]. 北京航空航天大学学报, 2019, 45(9): 1848-1854. doi: 10.13700/j.bh.1001-5965.2018.0739
引用本文: 谢颖贤, 武迎春, 王玉梅, 等 . 基于小波域清晰度评价的光场全聚焦图像融合[J]. 北京航空航天大学学报, 2019, 45(9): 1848-1854. doi: 10.13700/j.bh.1001-5965.2018.0739
XIE Yingxian, WU Yingchun, WANG Yumei, et al. Light field all-in-focus image fusion based on wavelet domain sharpness evaluation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(9): 1848-1854. doi: 10.13700/j.bh.1001-5965.2018.0739(in Chinese)
Citation: XIE Yingxian, WU Yingchun, WANG Yumei, et al. Light field all-in-focus image fusion based on wavelet domain sharpness evaluation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2019, 45(9): 1848-1854. doi: 10.13700/j.bh.1001-5965.2018.0739(in Chinese)

基于小波域清晰度评价的光场全聚焦图像融合

doi: 10.13700/j.bh.1001-5965.2018.0739
基金项目: 

国家自然科学基金 61601318

山西省青年科技研究基金 201601D021078

山西省重点学科建设经费项目 

山西省互联网+3D打印协同创新中心 

山西省“1331工程”重点创新团队 

山西省科技创新团队 201705D131025

太原科技大学博士启动基金 20132023

国家留学基金 

详细信息
    作者简介:

    谢颖贤  男, 硕士研究生。主要研究方向:光信息获取与处理

    武迎春  女, 博士, 副教授, 硕士生导师。主要研究方向:光信息获取与处理、光学三维传感

    通讯作者:

    武迎春, E-mail: yingchunwu3030@foxmail.com

  • 中图分类号: TN911

Light field all-in-focus image fusion based on wavelet domain sharpness evaluation

Funds: 

National Natural Science Foundation of China 61601318

Shanxi Province Science Foundation for Youths 201601D021078

the Fund of Shanxi Key Subjects Construction 

the Collaborative Innovation Center of Internet+3D Printing in Shanxi Province 

Key Innovation Team of Shanxi 1331 Project 

Scientific and Technological Innovation Team of Shanxi Province 201705D131025

Youth Foundation of Taiyuan University of Science and Technology 20132023

Foundation of China Scholarship Council 

More Information
  • 摘要:

    传统全聚焦图像融合以相机多次曝光拍摄的多聚焦图像为基础,光场相机在单次曝光后可计算空间任意深度的重聚焦图像,为后期全聚焦图像的获取提供便利。提出了一种基于小波变换的光场全聚焦图像获取算法,可有效避免传统空域图像融合算法的块效应,获得较高质量的全聚焦图像。该算法通过对微透镜阵列光场相机获得的4D光场数据进行空间变换与投影,得到用于全聚焦图像融合的重聚焦图像,对各帧重聚焦图像进行小波分解提取高、低频子图像集,提出区域均衡拉普拉斯算子、像素可见度函数分别构建融合图像的高、低频小波系数实现图像融合,其性能优于传统的区域清晰度评价函数。实验验证了所提算法的正确性和有效性,采用Lytro光场相机的原始数据计算了融合全聚焦图像,与传统图像融合算法相比,人眼视觉效果更好,客观图像指标也得到了提高。

     

  • 图 1  双平面参数化模型

    Figure 1.  Two-plane parametric model

    图 2  光场相机数字重聚焦原理

    Figure 2.  Digital refocusing principle of light field camera

    图 3  光场全聚焦图像融合流程

    Figure 3.  Procedure of light field all-in-focus image fusion

    图 4  基于拉普拉斯算子的高频子图像清晰度评价

    Figure 4.  High-frequency sub-image sharpness evaluation based on Laplace operator

    图 5  基于本文算法的Leaves样本图像融合

    Figure 5.  Image Leaves fusion based on proposed algorithm

    图 6  Flower样本图像不同融合算法对比

    Figure 6.  Comparison of different fusion algorithms based on image Flower

    图 7  Forest样本图像不同融合算法对比

    Figure 7.  Comparison of different fusion algorithms based on image Forest

    图 8  Zither样本图像不同融合算法对比

    Figure 8.  Comparison of different fusion algorithms based on image Zither

    表  1  Flower样本图像不同融合算法性能指标比较

    Table  1.   Comparison of performance indices of different fusion algorithms based on image Flower

    算法 E AG FD EI
    Sobel算法 6.867 6 6.247 0 6.899 1 66.534 0
    Prewitt算法 6.863 4 5.832 6 6.327 0 62.642 0
    Laplace算法 6.883 0 6.866 8 7.683 7 72.307 3
    本文算法 6.889 6 7.005 5 7.849 8 73.720 3
    下载: 导出CSV

    表  2  Forest样本图像不同融合算法性能指标比较

    Table  2.   Comparison of performance indices of different fusion algorithms based on image Forest

    算法 E AG FD EI
    Sobel算法 5.754 4 2.532 8 2.913 6 26.515 7
    Prewitt算法 5.749 2 2.290 5 2.576 6 24.273 5
    Laplace算法 5.801 1 3.001 8 3.523 5 31.013 4
    本文算法 5.809 9 3.087 5 3.630 5 31.903 3
    下载: 导出CSV

    表  3  Zither样本图像不同融合算法性能指标比较

    Table  3.   Comparison of performance indices of different fusion algorithms based on image Zither

    算法 E AG FD EI
    Sobel算法 6.293 5 4.467 5 5.186 5 48.385 4
    Prewitt算法 6.269 5 4.018 4 4.518 2 43.756 6
    Laplace算法 6.271 6 4.864 9 5.677 3 52.447 4
    本文算法 6.298 7 4.942 5 5.794 0 53.150 1
    下载: 导出CSV
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出版历程
  • 收稿日期:  2018-12-18
  • 录用日期:  2019-03-29
  • 刊出日期:  2019-09-20

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