非刚体图像配准中一种改进的点匹配方法

doi:10.16182/j.issn1004731x.joss.21-0073

系统仿真学报 ›› 2022, Vol. 34 ›› Issue (7): 1482-1489.doi: 10.16182/j.issn1004731x.joss.21-0073

非刚体图像配准中一种改进的点匹配方法

上官晋太¹(), 党雅文², 连玮¹

^1.长治学院计算机系，山西长治 046011
^2.中国科学院空天信息创新研究院，北京 100190

收稿日期:2021-01-25 修回日期:2021-04-20 出版日期:2022-07-30 发布日期:2022-07-20
作者简介:上官晋太（1964-）男，博士，副教授，研究方向为数字图像处理。E-mail：937214035@qq.com
基金资助:
国家自然科学基金(61773002);山西省高等学校教学改革创新项目(J2018181)

A Modified Point Matching Method for Non-Rigid Image Registration

Jintai Shangguan¹(), Yawen Dang², Wei Lian¹

^1.Dept. of Computer Science and Technology, Changzhi College, Changzhi 046011, China
^2.Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China

Received:2021-01-25 Revised:2021-04-20 Online:2022-07-30 Published:2022-07-20

摘要/Abstract

摘要：

为了解决在非刚体点匹配过程中，由于点集之间相对位置变化的复杂性，导致配准结果易收敛于局部最小值点的问题，提出了基于预中心配准的非刚体点匹配联合估计法。在用迭代最近点算法确定两个点集中的点之间的对应关系前，通过预先进行两个点集的中心配准的方法，可以更加合理地确定点之间的对应关系，从而使匹配结果可以最大程度地收敛于全局最优点。仿真实验表明，此方法和传统算法相比，在没有明显增加运算量的前提下，匹配效果更佳。

关键词: 非刚体点匹配, 对应关系, 联合估计, 中心预配准, 迭代最近点

Abstract:

Aiming at the problem that the registration results tend to converge to local minima due to the complexity of the relative position changes between two point sets in the non-rigid body point matching process, a joint estimation method for non-rigid body point matching based on precenter alignment is proposed, a modified matching method for non-rigid image registration based on centre preregistration is proposed. To better achieve the point matching accuracy between two point sets, a centre preregistration step is applied before the iterative closest point matching algorithm, which converges to a solution more close to a global optimum and thus better matching results. The simulation results show that the proposed method achieves better matching accuracy than the traditional algorithm without significantly increased computation.

Key words: non-rigid point matching, correspondence relationship, joint estimation, centre preregistration, iterative closest point

中图分类号:

TP391.4

上官晋太, 党雅文, 连玮. 非刚体图像配准中一种改进的点匹配方法[J]. 系统仿真学报, 2022, 34(7): 1482-1489.

Jintai Shangguan, Yawen Dang, Wei Lian. A Modified Point Matching Method for Non-Rigid Image Registration[J]. Journal of System Simulation, 2022, 34(7): 1482-1489.

图/表 10

图1

图2

图3

图4

图5

图6

图7

表1

表2

表3

参考文献 15

1	汤雯洁, 李若桐, 邓雪松, 等. ICP优化下的B样条四维CT图像弹性配准方法[J]. 系统仿真学报, 2020, 32(7):1301-1311.
	Tang Wenjie, Li Ruotong, Deng Xuesong, et al. ICP Optimized B-Spline Non-Rigid Rigistration for 4D-CT Images[J]. Journal of System Simulation, 2020, 32(7).1301-1311.
2	Kybic Jan, Vnucko Ian. Approximate all Nearest Neighbor Search for High Dimensional Entropy Estimation for Image Registration[J]. Signal Process (S0165-1684), 2012, 92(5): 1302-1316.
3	Ma Jiayi, Zhao Ji, Alan L, et al. Non-rigid Point Set Registration by Preserving Global and Local Structures [J]. IEEE Transactions on Image Processing (S1057-7149), 2016, 25(1): 53-64.
4	Haili Chui, Rangarajan Anand. A new Point Matching Algorithm for Non-rigid Registration[J]. Computer Vision and Image Understanding (S1077-3142), 2003, 89:114-141.
5	黄滢, 陈建胜, 汪承义.有约束Patch-Match框架下的非刚体匹配算法[J]. 中国图象图形学报,2018, 23(10): 1518-1529.
	Huang Ying, Chen Jiansheng, Wang Chengyi. Improved Non-rigid Matching Algorithm Under the Framework of Constrained Patch-match[J]. Journal of Image and Graphics, 2018, 23(10): 1518-1529.
6	Ma Jiayi, Jiang Junjun, Zhou Huabing, et al. Guided Locality Preserving Feature Matching for Remote Sensing Image Registration[J]. IEEE Transactions on Geoscience and Remote Sensing (S0196-2892), 2018, 56(8): 4435-4447.
7	Ma Jiayi, Chen Chen, Li Chang, et al. Infrared and Visible Image Fusion via Gradient Transfer and Total Variation Minimization[J]. Information Fusion (S1566-2535), 2016, 31: 100-109.
8	王丽芬, 成茜, 秦品乐, 等.基于多层P样条和稀疏编码的非刚性医学图像配准方法[J]. 计算机应用研究, 2018, 35(8): 2557-2560.
	Wang Lifen, Cheng Xi, Qin Pinle, et al. Non-Rigid Medical Image Registration Based on Multilayer P-Spline and Sparse Coding[J]. Application Research of Computers, 2018, 35(8): 2557-2560.
9	顾菊平, 程天宇, 华亮, 等. 面向脊柱生物建模的图像分割与配准综述[J]. 系统仿真学报, 2019, 31(2): 167-173.
	Gu Juping, Cheng Tianyu, Hua Liang, et al. Overview of Image Segmentation and Registration for Spine Biological Modeling[J]. Journal of System Simulation, 2019, 31(2): 167-173.
10	王雷, 郭全. 一种基于DCWPSO算法与FFD模型的心脏CT序列图像配准算法[J]. 山东理工大学学报(自然科学版), 2018, 32(1): 1-4.
	Wang Lei, Guo Quan. Sequenced Cardiac CT Image Registration Based on DCWPSO Algorithm and FFD model[J]. Journal of Shangdong University of Technology (Natural Science Edition), 2018, 32(1): 1-4.
11	Paul J, Neil D McKay Besl. A Method for Registration of 3-D Shapes[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence (S0162-8828), 1992, 14(2): 239-256.
12	刘世光, 王海荣, 刘锦. 快速四点一致性点云粗配准算法[J]. 山东大学学报(工学版), 2019, 49(2): 1-7.
	Liu Shiguang, Wang Hairong, Liu Jin. Fast 4-points Congruent Sets for Coarse Registration of 3D Point Cloud[J]. Journal of Shandong University (Engineering Science), 2019, 49(2): 1-7.
13	韩宝昌, 曹俊杰, 苏志勋.一种区域层次上的自动点云配准算法[J]. 计算机辅助设计与图形学学报, 2015, 27(2):313-319.
	Han Baochang, Cao Junjie, Su Zhixun. Automatic Point Clouds Registration Based on Regions[J]. Journal of Computer-Aided Design & Computer Graphics, 2015,27(2): 313-319.
14	石爱军, 白瑞林, 田青华, 等.遗传算法结合自适应阈值约束的ICP算法[J]. 光学技术, 2018, 44(1): 63-68.
	Shi Aijun, Bai Ruilin, Tian Qinghua, et al. Optimized ICP Method Combining Genetic Algorithm with Adaptive Threshold Constraints[J]. OPTICAL TECHNIQUE, 2018, 44(1): 63-68.
15	张春雷, 戴丽, 刘宇, 等.基于三点法和ICP算法的手术导航系统患者配准[J]. 东北大学学报(自然科学版), 2020, 41(11): 1584-1590.
	Zhang Chunlei, Dai Li, Liu Yu, et al. Patient Registration for Surgical Navigation System Based on Three-Point Method and ICP Algorithm[J]. Journal of Northeastern University(Natural Science), 2020, 41(11): 1584-1590.

图集	均值	方差
1	0.035 7	0.029 2
2	0.021 1	0.000 6
3	0.071 6	0
4	0.063 6	0
5	0.022 9	0.006 4
6	0.035 0	0.000 1
7	0.034 4	0.000 6
8	0.042 4	0

图集	均值	方差
1	0.159 1	0.000 3
2	0.042 3	0.001 3
3	0.318 2	0
4	0.235 0	0
5	0.038 0	0
6	0.223 4	0.001 4
7	0.170 2	0.001 1
8	0.119 8	0

图集	a
1	4.456 6
2	2.004 7
3	4.444 1
4	3.695 0
5	1.659 4
6	6.382 9
7	4.947 7
8	2.825 5

[1]	魏亮, 薛牧遥, 霍炬, 张金杰. 基于ICP算法的非合作目标特征点云配准优化[J]. 系统仿真学报, 2020, 32(12): 2383-2387.
[2]	顾菊平, 程天宇, 王建平, 华亮, 赵凤申, 蒋凌. 基于几何特征不变量的快速3D医学图像配准[J]. 系统仿真学报, 2020, 32(11): 2105-2111.

非刚体图像配准中一种改进的点匹配方法

A Modified Point Matching Method for Non-Rigid Image Registration

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 10

参考文献 15

相关文章 2

编辑推荐

Metrics

本文评价