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Visible and infrared image registration based on region features and edginess

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Abstract

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.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (Nos. 61231016, 61303123, 61273265), the Natural Science Foundation of Shaanxi Province (No. 2015JQ6256), the Fundamental Research Funds for the Central Universities (No. 3102015JSJ0008).

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Authors and Affiliations

  1. School of Computer Science, Northwestern Polytechnical University, Xi’an, China

    Yanjia Chen, Xiuwei Zhang, Yanning Zhang & Zhipeng Fu

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

    Stephen John Maybank

  3. Henan University of Science and Technology, Luoyang, China

    Zhipeng Fu

Authors
  1. Yanjia Chen
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  2. Xiuwei Zhang
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  3. Yanning Zhang
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  4. Stephen John Maybank
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  5. Zhipeng Fu
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Correspondence to Xiuwei Zhang.

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Chen, Y., Zhang, X., Zhang, Y. et al. Visible and infrared image registration based on region features and edginess. Machine Vision and Applications 29, 113–123 (2018). https://doi.org/10.1007/s00138-017-0879-6

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  • DOI: https://doi.org/10.1007/s00138-017-0879-6

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