A Regenerated Feature Extraction Method for Cross-modal Image Registration

doi:10.1007/978-3-030-00563-4_43

CORC > 西安光学精密机械研究所 > 中国科学院西安光学精密机械研究所 > 光学影像学习与分析中心

	A Regenerated Feature Extraction Method for Cross-modal Image Registration
	Yang, Jian 1; Wang, Qi 1,2; Li, Xuelong 3
	2018
会议日期	2018-07-07
会议地点	Xi'an, China
卷号	10989 LNAI
DOI	10.1007/978-3-030-00563-4_43
页码	441-451
英文摘要	Cross-modal image registration is an intractable problem in computer vision and pattern recognition. Inspired by that human gradually deepen to learn in the cognitive process, we present a novel method to automatically register images with different modes in this paper. Unlike most existing registrations that align images by single type of features or directly using multiple features, we employ the “regenerated” mechanism cooperated with a dynamic routing to adaptively detect features and match for different modal images. The geometry-based maximally stable extremal regions (MSER) are first implemented to fast detect non-overlapping regions as the primitive of feature regeneration, which are used to generate novel control-points using salient image disks (SIDs) operator embedded by a sub-pixel iteration. Then a dynamic routing is proposed to select suitable features and match images. Experimental results on optical and multi-sensor images show that our method has a better accuracy compared to state-of-the-art approaches. © 2018, Springer Nature Switzerland AG.
产权排序	3
会议录	Advances in Brain Inspired Cognitive Systems - 9th International Conference, BICS 2018, Proceedings
会议录出版者	Springer Verlag
语种	英语
ISSN号	03029743;16113349
ISBN号	9783030005627
内容类型	会议论文
源URL	[http://ir.opt.ac.cn/handle/181661/30687]
专题	西安光学精密机械研究所_光学影像学习与分析中心
通讯作者	Wang, Qi
作者单位	1.School of Computer Science and Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University, Xi’an; Shaanxi; 710072, China; 2.Unmanned System Research Institute (USRI), Northwestern Polytechnical University, Xi’an; Shaanxi; 710072, China; 3.Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Science, Xi’an; Shaanxi; 710119, China
推荐引用方式 GB/T 7714	Yang, Jian,Wang, Qi,Li, Xuelong. A Regenerated Feature Extraction Method for Cross-modal Image Registration[C]. 见:. Xi'an, China. 2018-07-07.