基于传感器参数和目标轮廓 中心的自动配准算法研究

刘松涛; 王学伟; 周晓东; 王成刚

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基于传感器参数和目标轮廓中心的自动配准算法研究

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- 基于传感器参数和目标轮廓中心的自动配准算法研究
- Automatic registration algorithm based on sensor parameters and target's contour centroid
- 光学精密工程 2005年13卷第3期页码：354-363
- 作者机构：
  
  海军航空工程学院控制工程系,山东烟台,264001
- 作者简介：
- 基金信息：
- DOI：
  中图分类号： TH391.4
- 收稿日期：2005-02-16，
  
  修回日期：2005-04-16，
  
  网络出版日期：2005-06-30，
  
  纸质出版日期：2005-06-30
- 稿件说明：
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刘松涛, 王学伟, 周晓东, 等. 基于传感器参数和目标轮廓中心的自动配准算法研究[J]. 光学精密工程, 2005,13(3):354-363.

LIU Song-tao, WANG Xue-wei, ZHOU Xiao-dong, et al. Automatic registration algorithm based on sensor parameters and target's contour centroid[J]. Optics and precision engineering, 2005, 13(3): 354-363.
刘松涛, 王学伟, 周晓东, 等. 基于传感器参数和目标轮廓中心的自动配准算法研究[J]. 光学精密工程, 2005,13(3):354-363. DOI：

LIU Song-tao, WANG Xue-wei, ZHOU Xiao-dong, et al. Automatic registration algorithm based on sensor parameters and target's contour centroid[J]. Optics and precision engineering, 2005, 13(3): 354-363. DOI：

摘要

通过对光电成像型反舰导弹的成像过程分析

提出了一种自动配准算法。其基本思路是将图像变换模型分解

逐步简化。可见光和红外图像配准时的变换为仿射变换。首先

利用传感器参数的调整

消除图像间的比例变化

将仿射变换简化为刚体变换;然后

依赖图像信息

用形态学边缘检测的方法求取目标的轮廓中心

以此为控制点消除图像间的平移变化

实现图像的完全配准;最后

通过观察海天线是否重合以及利用均方根误差原则

对算法的配准效果做详细评估。仿真实验表明

该算法准确、快速

配准精度满足目标识别的要求

可以较好地解决异类传感器弱小目标图像配准的难题。

Abstract

Based on the analysis of the imaging process of optoelectronic imaging anti-ship missile

an automatic registration algorithm is proposed

and its basic idea is to decompose the transform model and simplify it step by step. Originally

the distortion between infrared and visible images is affine. First

by adjusting sensor parameters

the scaling change between images is eliminated and the affine transform is simplified into rigid transform. Then depending on image information

the centroid of the target's contour is computed by morphological edge detection and chosen as control point

which is used to eliminate the translational change between images and achieve the complete alignment. Finally

the registration effect is assessed by judging whether the sea-sky-lines of the two registered images are superposed and using the rule of root mean square error. The simulation experiments convince that the algorithm is accurate

fast

and can meet the precision requirement for target recognition

providing a good way for solving the difficult registration problem of small target images with different sensors.

关键词

Keywords

references

. BROWN L. A survey of image registration techniques[J]. ACM Computing Surveys, 1992, 24(4): 325-376.

. ZITOVA B,FLUSSER J. Image registration methods:a survey[J]. Image and Vision Computing, 2003, 21: 977-1000.

. 罗诗途, 王艳玲, 张玘,等. 车载图像跟踪系统中电子稳像算法的研究[J]. 光学精密工程, 2005, 13(1): 95-103. LUO SH T, WANG Y L, ZHANG Q, et al. Electronic image stabilizing algorithm for image tracking system on vehicle [J]. Optics and Precision Engineering, 2005, 13(1): 95-103. ( in Chinese)

. BERNEA D I. A class of algorithms for fast digital image registration[J]. IEEE Transactions on Computer, 1972, 21(2): 179-186.

. 徐瑞鑫, 刘伟宁. 基于自适应模板的实时跟踪算法[J]. 光学精密工程, 2002, 10(4): 365-369. XU R X, LIU W N. Adaptive model- based real time tracking algorithm[J]. Optics and Precision Engineering, 2002, 10(4): 365-369. ( in Chinese)

. DAI X L,KHORRAM S. A feature-based image registration algorithm using improved chain-code representation combined with invariant moments[J]. IEEE Transactions on Geoscience and Remote Sensing, 1999, 37(5): 2351-2362.

. REDDY B S, CHATTERJI B N. An FFT-based technique for translation, rotation, and scale in variant image registration[J]. IEEE Transactions on Image Processing, 1996, 5(8): 1266-1271.

. VIOLA P A,WELLS W M. Alignment by maximization of mutual information . Proc. 5th Int. Conf. Computer Vision, Bosto, MA, 1995:16-23.

. VIOLA P A,WELLS W M. Alignment by maximization of mutual information[J]. International Journal of Computer Vision, 1997, 24(2): 137-154.

. COLLIGNON A,MAES F,DELAERE D,et al. Automated multimodality image registration based on information theory . Proc. Information Processing in Medical Imaging Conference, Norwell, MA,Kluwer, 1995:263-274.

. 钮永胜, 倪国强. 基于小波分析的可见光图像自动配准方法研究[J]. 高技术通讯, 1999,9(9):24-27. NIU Y SH, NI G Q. Research on automated image registration technique for visual image based on wavelet analysis[J]. High Technique Communication, 1999,9(9):24-27. (in Chinese)

. 张泽旭, 李金宗, 李冬冬. 基于光流场分析的红外图像自动配准方法研究[J]. 红外与毫米波学报, 2003, 22(4): 307-312. ZHANG Z X, LI J Z, LI D D. Research of automated image registration technique for infrared images based on optical flow field analysis[J]. Journal of Infrared and Millimeter Waves, 2003, 22(4): 307-312. (in Chinese)

. JUNG I K,LACROIX S. A robust interest points matching algorithm . Proceedings of Eighth IEEE International Conference on Computer Vision, Vancouver, BC, Canada, 2001, 2: 538-543.

. 谌安军, 陈炜, 毛士艺. 一种基于边缘的图像配准方法 . 电子与信息学报, 2004, 26(5): 679-684. ZHAN A J, CHEN W, MAO S Y. An image edge based algorithm for multisensor image registration[J]. Journal of Electronics and Information Technology, 2004, 26(5): 679-684. (in Chinese)

. LI H,MANJUNATH B S. A contour based approach to multi-sensor image registration[J]. IEEE Transactions on Image Processing, 1995, 4(3): 320-334.

. TRASK D,CANNATA R, HACKETT J K. Automated model-based image registration for tactical image exploitation[J]. SPIE,2000,4054:19-29.

. 刘松涛,沈同圣,韩艳丽,等. 舰船目标海天线提取方法研究[J]. 激光与红外,2003,33(1):51-53. LIU S T, SHEN T S, HAN Y L, et al. Research on locating the horizontal region of ship target[J]. Laser and Infrared, 2003, 33(1): 51-53. (in Chinese)

. LEHMANN T M,GONNER C,SPITZER K. Survey: interpolation methods in medical image processing[J]. IEEE Transactions on Medical Imaging, 1999, 18(11): 1049-1075.

. 徐东燕, 付忠良, 阮波. 一种基于多结构元的弱对比度图像的边缘检测方法[J]. 计算机应用, 2004, 24(6): 108-110. XU D Y, FU ZH L, RUAN B. An approach of low contrast image edge detection based on multi morphological structuring elements[J]. Computer Applications, 2004, 24(6): 108-110. (in Chinese)

. SAHOO P K,SOLTANI S,WONG A K C. A survey of thresholding techniques[J]. Computer Vision Graphics Image Process, 1988, 41:223-260.

. 丘江,杨静,刘波. 基于TMS320C50的图像目标分割系统 . 电子技术应用,2001,12:62-64. QIU J, YANG J, LIU B. Image target segmentation system based on TMS320C50[J]. Electronic Technique Application, 2001, (12): 62-64. (in Chinese)

. THEVENAZ P,RUTTIMANN U E,UNSER M. A pyramid approach to subpixel registration based on intersity[J]. IEEE Trans.Image Processing, 1998, 7: 27-41.

. THEVENAZ P,UNSER M. Optimization of mutual information for multiresolution image registration[J]. IEEE Trans. Image Processing, 2000, 9: 2083-2099.

. KERN J P. Reliable band-to-band registration of multi-spectral thermal image data using multivariate mutual information and cyclic consistency[J].SPIE,2004,5558:57-68.

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