Format: TXT, ZIPPublisher: IEEE DataPortPublication Date of the Electronic Edition: 11/12/2025
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ISBN: 10.21227/dtt8-vh83
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Description
In this dataset, we present a novel RGB-Thermal paired dataset, RGBT-1K, comprising 1,000 image pairs specifically curated to support research in multi-modality image processing. The dataset captures diverse indoor and outdoor scenes under varying lighting conditions, offering a robust benchmark for applications in image enhancement, object detection, and scene analysis. The image acquisition process involved using the FLIR A70 thermal camera and the Sony Handycam HDR-CX405, with the latter positioned atop the thermal camera for precise alignment. The dataset then goes through image registration and transformation steps to better align it pixel by pixel for training in learning-based approaches. This setup ensured synchronized RGB and thermal captures, allowing for accurate multi-modal data analysis. Potential applications of this dataset span a wide range of computer vision tasks, including surveillance, autonomous navigation, and medical imaging, making it a valuable resource for academia and industry.If you use the dataset please cite the published articleS. K. Panda and P. K. Sa, "A Thermal-Aware Multi-Sensor Framework for Low-Light Image Enhancement," in IEEE Sensors Journal, doi: 10.1109/JSEN.2025.3590815.
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