一种改进的基于奇异值分解的亚像素级图像配准算法

doi:10.7523/j.issn.2095-6134.2019.01.014

中国科学院大学学报 ›› 2019, Vol. 36 ›› Issue (1): 101-108.DOI: 10.7523/j.issn.2095-6134.2019.01.014

一种改进的基于奇异值分解的亚像素级图像配准算法

凌程, 耿修瑞, 杨炜暾, 赵永超

中国科学院电子学研究所中国科学院空间信息处理与应用系统技术重点实验室, 北京 100190;中国科学院大学, 北京 100049

收稿日期:2017-11-13 修回日期:2018-01-09 发布日期:2019-01-15
通讯作者: 凌程,E-mail:lingcheng15@mails.ucas.ac.cn
基金资助:
高分5号应用共性关键技术项目（30-Y20A28-9004-15/17）和国家重大科研仪器研制项目（41427805）资助

An improved subpixel image registration algorithm based on singular value decomposition

LING Cheng, GENG Xiurui, YANG Weitun, ZHAO Yongchao

Key Laboratory of Technology in Geo-spatial Information Processing and Application System of CAS, Institute of Electronics, Chinese Academy of Science, Beijing 100190, China;University of Chinese Academy of Science, Beijing 100049, China

Received:2017-11-13 Revised:2018-01-09 Published:2019-01-15

摘要/Abstract

摘要： 基于奇异值分解（SVD）的相位相关法是一种经典的具有亚像素级精度的图像配准算法，但当两幅待配准图的平移量较大或噪声较强时，该配准算法中的积分法得到的相位解缠结果往往不可靠。根据线性相位的单调变化特性，提出一种改进的相位解缠算法，通过比较相邻相位差和趋势斜率的一致性判断是否进行校正，从而得到真实相位值。针对真实光学图像的实验表明，该方法可以有效地对积分法所得到的结果进行校正，进而提高匹配精度。

关键词: 图像配准, 亚像素, 奇异值分解, 相位解缠, 积分法

Abstract: Phase correlation method based on singular value decomposition (SVD) is a known subpixel image registration algorithm. However, when the translation between two images to be registered is large or there is high noise, the phase unwrapping results obtained using the integral method in the registration algorithm are often unreliable. In this work, an improved phase unwrapping algorithm is proposed based on the monotonic variation of linear phase. By comparing the consistency of the adjacent phase differences and the trend slopes, the algorithm determines whether to make corrections, so as to get the real phase. Experiments on real optical images show that the proposed method effectively corrects the results obtained using the integral method, and hence increases matching accuracy.

Key words: image registration, subpixel, singular value decomposition, phase unwrapping, integral method

中图分类号:

TP391.41

凌程, 耿修瑞, 杨炜暾, 赵永超. 一种改进的基于奇异值分解的亚像素级图像配准算法[J]. 中国科学院大学学报, 2019, 36(1): 101-108.

LING Cheng, GENG Xiurui, YANG Weitun, ZHAO Yongchao. An improved subpixel image registration algorithm based on singular value decomposition[J]. , 2019, 36(1): 101-108.

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一种改进的基于奇异值分解的亚像素级图像配准算法

An improved subpixel image registration algorithm based on singular value decomposition

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