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Visible and infrared image registration based on region features and edginess

机译:基于区域特征和边缘的可见和红外图像配准

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摘要

Visible and infrared image registration is required for multi-sensor fusion and cooperative processing. However, traditional single-sensor image registration methods are generally not feasible as multi-sensor images are often loosely related and show different properties in imaging. This paper presents a coarse-to-fine procedure for registering visible and infrared images based on stable region features and edginess. Zernike moments are used to describe salient region features for a coarse registration, and an entropy optimal process based on edginess is used to refine the registration to achieve a more accurate result. Experiments show that the proposed method provides more robust and accurate registration than the existing methods.
机译:多传感器融合和协作处理需要可见和红外图像配准。但是,传统的单传感器图像配准方法通常不可行,因为多传感器图像通常松散相关并且在成像中显示不同的属性。本文提出了一种基于稳定区域特征和边缘感的从粗糙到精细的配准可见光和红外图像的方法。 Zernike矩用于描述粗略配准的显着区域特征,并且基于边缘的熵最佳过程用于细化配准以获得更准确的结果。实验表明,与现有方法相比,该方法具有更强的鲁棒性和准确性。

著录项

  • 来源
    《Machine Vision and Applications》 |2018年第1期|113-123|共11页
  • 作者单位

    School of Computer Science, Northwestern Polytechnical University, Xi'an, China;

    School of Computer Science, Northwestern Polytechnical University, Xi'an, China;

    School of Computer Science, Northwestern Polytechnical University, Xi'an, China;

    Department of Computer Science and Information Systems, Birkbeck College, University of London, London, UK;

    School of Computer Science, Northwestern Polytechnical University, Xi'an, China,Henan University of Science and Technology, Luoyang, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Multi-sensor; Image registration; Region features; Edginess;

    机译:多传感器图像配准;区域特征;尖锐;

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