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Multimodal image registration techniques: a comprehensive survey

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Abstract

This manuscript presents a review of state-of-the-art techniques proposed in the literature for multimodal image registration, addressing instances where images from different modalities need to be precisely aligned in the same reference system. This scenario arises when the images to be registered come from different modalities, among the visible and thermal spectral bands, 3D-RGB, or flash-no flash, or NIR-visible. The review spans different techniques from classical approaches to more modern ones based on deep learning, aiming to highlight the particularities required at each step in the registration pipeline when dealing with multimodal images. It is noteworthy that medical images are excluded from this review due to their specific characteristics, including the use of both active and passive sensors or the non-rigid nature of the body contained in the image.

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Data Availibility Statement

Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

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Acknowledgements

This material is based upon work supported by the Air Force Office of Scientific Research under award number FA9550-22-1-0261; and partially supported by the Grant PID2021-128945NB-I00 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe"; the “CERCA Programme / Generalitat de Catalunya"; and the ESPOL project CIDIS-12-2022.

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Authors and Affiliations

  1. FIEC, CIDIS, ESPOL Polytechnic University, Campus Gustavo Galindo, Guayaquil, 09-01-5863, Ecuador

    Henry O. Velesaca, Gisel Bastidas & Angel D. Sappa

  2. Software Engineering Department, University of Granada, Granada, 18014, Spain

    Henry O. Velesaca

  3. Escuela Superior Politécnica de Chimborazo, Panamerica Sur km 1 1/2, Riobamba, Ecuador

    Gisel Bastidas

  4. Inria Paris Centre, 2 Rue Simone Iff, Paris, 75012, France

    Mohammad Rouhani

  5. Computer Vision Center, Universitat Autónom de Barcelona, Bellaterra, Barcelona, 08193, Spain

    Angel D. Sappa

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Velesaca, H.O., Bastidas, G., Rouhani, M. et al. Multimodal image registration techniques: a comprehensive survey. Multimed Tools Appl 83, 63919–63947 (2024). https://doi.org/10.1007/s11042-023-17991-2

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