多特征红外光与可见光图像的分区域配准

王颖; 韩静文

doi:doi:10.3969/j.issn.1003-501x.2015.04.012

光电工程, 2015, 42 (4): 68, 网络出版: 2015-09-08

多特征红外光与可见光图像的分区域配准

Sub-regional Registration Based on Features of the Infrared and Visible Images

论文大纲

王颖 ^*韩静文

作者单位

北京化工大学信息科学与技术学院, 北京 100029

图像配准直线特征特征匹配 image registration line feature SURF SURF feature matching

摘要

针对发生较大角度旋转及平移时图像配准精度不高, 图像配准对局部形变和光照较为敏感的问题, 本文提出了基于直线和 SURF特征的图像分区域配准算法。首先利用 Hough变换实现图像的粗配准; 然后对图像进行分区, 在子区域内利用 SURF算子求取变换模型参数, 完成图像的配准。实验表明该方法可用于红外与可见光图像的配准, 与传统方法相比, 本方法能够在图像存在大角度旋转和平移时实现高精度配准, 且在图像存在局部形变及光照不均时精度较好。

Abstract

An algorithm of image registration based on Hough transform and SURF features is proposed, to solve the problem that the accuracy is low in image registration when large angle rotation and translation occur, and the problem that traditional method is sensitive about local deformation and uneven illumination. Firstly, Hough transform is used to extract straight line features to estimate the rotation and translation parameters to achieve a rough image registration. Then, the image is divided into a few parts, and the SURF is used to do the precisely match sub-regionally. Finally, matching parameters are calculated and the registration is accomplished. Experiments show that the method can be used in the registration of IR and VI images, compared with traditional methods, and this method can achieve higher accuracy in the presence of a large angle rotation and translation and get a better result when localized deformation or uneven illumination is occurring.

参考文献

[1] 芮挺, 张升奡, 周遊, 等. 具有 SIFT描述的 Harris角点多源图像配准[J].光电工程, 2012, 39(8): 26-31. RUI Ting, ZHANG Sheng′ao, ZHOU You, et al. Registration of Multi-sensor Images Based on Harris Corner with SIFT Description[J]. Opto-Electronic Engineering, 2012, 39(8): 26-31.

[2] 赵明, 林长青. 基于改进 SIFT特征的红外与可见光图像配准方法[J].光电工程, 2011, 38(9): 130-136. ZHAO Ming, LIN Changqing. Registration of Infrared and Visible Images Based on Improved SIFT Feature[J]. Opto-Electronic Engineering, 2011, 38(9): 130-136.

[3] Lowe D G. Distinctive Image Features from Scale-invariant Key points[J]. International Journal of Computer Vision(S1573-1405), 2004, 60(2): 91-110.

[4] 杜京义, 胡益民, 刘宇程. 基于区域分块的 SIFT图像匹配技术研究与实现[J].光电工程, 2013, 40(8): 52-58. DU Jingyi, HU Yimin, LIU Yucheng. Research and Implementation of Matching Technique of Image Based on SIFT Algorithm of Area Blocking[J]. Opto-Electronic Engineering, 2013, 40(8): 52-58.

[5] HERBERT B, TUVTELLARS T, LUC V G．SURF: Speeded Up Robust Features[C]// Computer Vision-ECCV, Graz, Austria, May7-13, 2006: 404-417．

[6] 张锐娟, 张建奇, 杨翠. 基于 SURF的图像配准方法研究[J].红外与激光工程, 2009, 38(1): 160-165. ZHANG Ruijuan, ZHANG Jianqi, YANG Cui. Image registration approach based on SURF[J]. Infrared and Laser Engineering, 2009, 38(1): 160-165.

[7] 乔勇军, 谢晓方, 李德栋, 等. SURF特征匹配中的分块加速方法研究[J]．激光与红外, 2011, 41(6): 691-696. QIAO Yongjun, XIE Xiaofang, LI Dedong, et al. Image Registration Approach Based on SURF[J]. Laser and Infrared, 2011, 41(6): 691-696.

[8] HAN J, PAUWELS E J, ZEEUW P D. Visible and infrared image registration in man-made environments employing hybrid visual features[J]. Pattern Recognition Letters(S0165-1684), 2013, 34(1): 42-51.

[9] BALLARD D H. Generalizing the Hough Transform to Detect Arbitrary Shapes[J]．Pattern Recognition(S0031-3203), 1981, 13(2): 111-122.

[10] WANG Peng, WANG Ping, QU Zhiguo, et al. A novel algorithm for visual and IR image registration based on Hough Transform[C]// Multi-Platform/Multi-Sensor Remote Sending and Mapping(M2RSM), 2011 International Workshop on IEEE, Xiamen, China, Jan 10-12, 2011: 1-4.

[11] Davis J W, Sharma V. Background-Subtraction using Contour-based Fusion of Thermal and Visible Imagery[J]. Computer Vision and Image Understanding(S1077-3142), 2007, 106(2): 162-182.

王颖, 韩静文. 多特征红外光与可见光图像的分区域配准[J]. 光电工程, 2015, 42(4): 68. WANG Ying, HAN Jingwen. Sub-regional Registration Based on Features of the Infrared and Visible Images[J]. Opto-Electronic Engineering, 2015, 42(4): 68.

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