引用本文: | 朱明,姚强,唐俊,等.超图约束和改进归一化互相关方法相结合的图像配准算法[J].国防科技大学学报,2019,41(3):50-55.[点击复制] |
ZHU Ming,YAO Qiang,TANG Jun,et al.Image registration algorithm with hypergraph constraint and improved normalized cross correlation method[J].Journal of National University of Defense Technology,2019,41(3):50-55[点击复制] |
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超图约束和改进归一化互相关方法相结合的图像配准算法 |
朱明1,2, 姚强1, 唐俊1, 张艳1 |
(1.安徽大学 电子信息工程学院, 安徽 合肥 230601;2.偏振光成像探测技术安徽省重点实验室, 安徽 合肥 230031)
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摘要: |
为提高图像配准算法的精度和适应能力,将超图约束和改进归一化互相关方法应用于图像配准。利用Hessian-Affine检测得到的仿射不变区域代替固定窗口来改进归一化互相关方法,获得初始匹配点对;通过马氏距离计算超边间的相似度,采用超图约束计算匹配分数对匹配对进行排序;利用分数高的部分匹配点对初始化变换矩阵,通过过滤匹配对来循环更新得到最优变换矩阵实现配准。实验结果表明,该方法具有较好的匹配和剔除错误匹配的效果,在不同类型的图像配准中也有较好的配准效果。 |
关键词: 图像配准 超图 仿射不变 马氏距离 |
DOI:10.11887/j.cn.201903009 |
投稿日期:2018-04-16 |
基金项目:国家自然科学基金资助项目(61501003,61401001,61772032,61672032);偏振光成像探测技术安徽省重点实验室开放课题资助项目(2016-KFJJ-002) |
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Image registration algorithm with hypergraph constraint and improved normalized cross correlation method |
ZHU Ming1,2, YAO Qiang1, TANG Jun1, ZHANG Yan1 |
(1.School of Electronics and Information Engineering, Anhui University, Hefei 230601, China;2.Key Laboratory of Polarization Imaging Detection Technology in Anhui Province, Hefei 230031, China)
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Abstract: |
In order to improve the accuracy and adaptability of image registration algorithm, the hypergraph constraint and the improved NCC(normalized cross correlation) were applied to image registration. The proposed algorithm used the Hessian Affine detection affine invariant region instead of the fixed window to improve the NCC method and obtained the initial matching point pairs. The similarity degrees between the hyperedges of hypergraph were calculated by Martensitic distance, and the matching scores of the matching pairs calculated by hypergraph constraint were used to sort the matching pairs. The transformation matrix was initialized with some matching points of higher matching scores, and was circularly updated by filtering matching pairs to get the optimal transformation matrix, which was used to implement registration. Experimental results show that the proposed method has better performance in matching and rejecting mismatch, and it also has better registration performance in different types of image registration. |
Keywords: image registration hypergraph affine invariance Mahalanobis distance |
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