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Authors: Enrique Heredia-Aguado ; Marcos Alfaro-Pérez ; María Flores ; Luis Paya ; David Valiente and Arturo Gil

Affiliation: University Institute for Engineering Research, Miguel Hernández University, Avda. de la Universidad s/n, 03202 Elche (Alicante), Spain

Keyword(s): Image Fusion, Multispectral Image, Object Detection, RGB-Thermal, Deep Learning.

Abstract: Fusing visible and thermal imagery is a promising approach for robust object detection in challenging environments, taking advantage of the strengths from different spectral information. Building on previous work in static early fusion, we present a comparative study of adaptative reprojection fusion methods that exploit advanced projections and frequency-domain transforms to combine RGB and thermal data. We evaluate Principal Component Analysis, Factor Analysis, Wavelet and Curvelet-based fusion, all integrated into a YOLOv8 detection pipeline. Experiments are conducted on the LLVIP dataset, with a focus on methodological rigour and reproducibility. This research show promising results based on these methods comparing to previous early fusion methods. We discuss the implications for future research and the value of robust experimental design for advancing the state of the art in multispectral fusion.

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Paper citation in several formats:
Heredia-Aguado, E., Alfaro-Pérez, M., Flores, M., Paya, L., Valiente, D. and Gil, A. (2025). A Robust Comparative Study of Adaptative Reprojection Fusion Methods for Deep Learning Based Detection Tasks with RGB-Thermal Images. In Proceedings of the 22nd International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-770-2; ISSN 2184-2809, SciTePress, pages 313-320. DOI: 10.5220/0013761800003982

@conference{icinco25,
author={Enrique Heredia{-}Aguado and Marcos Alfaro{-}Pérez and María Flores and Luis Paya and David Valiente and Arturo Gil},
title={A Robust Comparative Study of Adaptative Reprojection Fusion Methods for Deep Learning Based Detection Tasks with RGB-Thermal Images},
booktitle={Proceedings of the 22nd International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2025},
pages={313-320},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013761800003982},
isbn={978-989-758-770-2},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 22nd International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - A Robust Comparative Study of Adaptative Reprojection Fusion Methods for Deep Learning Based Detection Tasks with RGB-Thermal Images
SN - 978-989-758-770-2
IS - 2184-2809
AU - Heredia-Aguado, E.
AU - Alfaro-Pérez, M.
AU - Flores, M.
AU - Paya, L.
AU - Valiente, D.
AU - Gil, A.
PY - 2025
SP - 313
EP - 320
DO - 10.5220/0013761800003982
PB - SciTePress

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