Synthetic Thermal Image Generation from Multi-Cue Input Data

Patricia Suárez, Angel Sappa, Angel Sappa

2025

Abstract

This paper presents a novel approach for generating synthetic thermal images using depth and edge maps from the given grayscale image. In this way, the network receives the fused image as input to generate a synthetic thermal representation. By training a generative model with the depth map fused with the corresponding edge representation, the model learns to generate realistic synthetic thermal images. A study on the correlation between different types of inputs shows that depth and edge maps are better correlated than grayscale images, or other options generally used in the state-of-the-art approaches. Experimental results demonstrate that the method outperforms state-of-the-art and produces better-quality synthetic thermal images with improved shape and sharpness. Improvements in results are attributed to the combined use of depth and edge maps together with the novel loss function terms proposed in the current work.

Paper Citation

in Harvard Style

Suárez P. and Sappa A. (2025). Synthetic Thermal Image Generation from Multi-Cue Input Data. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP; ISBN 978-989-758-728-3, SciTePress, pages 275-282. DOI: 10.5220/0013092100003912

in Bibtex Style

@conference{visapp25,
author={Patricia Suárez and Angel Sappa},
title={Synthetic Thermal Image Generation from Multi-Cue Input Data},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP},
year={2025},
pages={275-282},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013092100003912},
isbn={978-989-758-728-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP
TI - Synthetic Thermal Image Generation from Multi-Cue Input Data
SN - 978-989-758-728-3
AU - Suárez P.
AU - Sappa A.
PY - 2025
SP - 275
EP - 282
DO - 10.5220/0013092100003912
PB - SciTePress