基于超分辨率重建的亚像素图像配准

李方彪; 何昕; 魏仲慧; 马鑫

doi:10.3788/OPE.20172402.0477

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基于超分辨率重建的亚像素图像配准

信息科学 | 更新时间：2020-07-07

- 基于超分辨率重建的亚像素图像配准
- Sub-pixel image registration based on super resolution reconstruction
- 光学精密工程 2017年25卷第2期页码：477-484
- 作者机构：
  
  1.中国科学院长春光学精密机械与物理研究所, 吉林长春 130033
  2.中国科学院大学, 北京 100049
- 作者简介：
  
  李方彪 (1990-), 男, 湖南郴州人, 博士研究生, 2013年于湖南大学获得学士学位, 主要从事数字图像处理方面的研究。E-mail:lifangbiao1215@163.com LI Fang-biao, E-mail: lifangbiao1215@163.com
  [ "何昕 (1966-)，男，吉林长春人，研究员，博士生导师，主要从事图像处理、光电测量等方面的研究。E-mail: hexin6627@sohu.com" ]
- 基金信息：
  
  国家自然科学基金资助项目(60878052)
- DOI：10.3788/OPE.20172402.0477
  中图分类号： TP391.4
- 收稿日期：2016-07-21，
  
  录用日期：2016-9-20，
  
  纸质出版日期：2017-02-25
- 稿件说明：
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李方彪, 何昕, 魏仲慧, 等. 基于超分辨率重建的亚像素图像配准[J]. 光学精密工程, 2017,25(2):477-484.

Fang-biao LI, Xin HE, Zhong-hui WEI, et al. Sub-pixel image registration based on super resolution reconstruction[J]. Optics and precision engineering, 2017, 25(2): 477-484.
李方彪, 何昕, 魏仲慧, 等. 基于超分辨率重建的亚像素图像配准[J]. 光学精密工程, 2017,25(2):477-484. DOI： 10.3788/OPE.20172402.0477.

Fang-biao LI, Xin HE, Zhong-hui WEI, et al. Sub-pixel image registration based on super resolution reconstruction[J]. Optics and precision engineering, 2017, 25(2): 477-484. DOI： 10.3788/OPE.20172402.0477.

摘要

针对低分辨率图像在配准过程中精度较低的问题，提出了一种基于超分辨率重建的亚像素图像配准方法。首先，对具有1至9像素位移的图像序列进行10倍降采样，获取具有0.1至0.9亚像素位移的图像序列。然后，根据图像的获取过程建立数学模型，以Bayes理论为基础，使用最大后验概率法（MAP）对亚像素位移低分辨率图像进行超分辨率重建，获取高分辨率图像。最后，使用具有亚像素配准精度的扩展相位相关法对图像进行配准。配准实验与噪声实验表明，所提方法的最大配准误差为0.03 pixel，能实现对低分辨率图像的亚像素级配准，具有配准精度高、噪声抗干扰能力强等特点，可同时满足可见光图像与红外图像的高精度配准要求。

Abstract

Considering the low precision of low-resolution image used for the registration process

a sub-pixel image registration method based on super resolution reconstruction was put forward. Firstly

10 times down-sampling was carried out in the image sequence with 1~9 pixel displacement to obtain an image sequence with 0.1~0.9 sub-pixel displacement; then

a mathematical model was built in accordance with the image acquisition process

and Maximum A-Posteriori (MAP) method was used to carry out super resolution reconstruction in low-resolution image of the sub-pixel displacement to obtain high-resolution image based on the Bayes Theory; finally

the extended phase correlation method with sub-pixel registration accuracy was applied to conduct image registration. The registration and noise experiments inclicate that the maximum registration error is 0.03 pixel. The proposed method has high registration accuracy and strong anti-noise ability. It can realize the sub-pixel registration for low-resolution image

at the same time

it can meet the requirements for high-accuracy registration of visible image and infrared image.

关键词

Keywords

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