A Basic Tool for Improving Bad Illuminated Archaeological Pictures

Michela Lecca

2023

Abstract

Gathering visual documentation of archaeological sites and monuments helps monitor their status and preserve and transmit the memory of the cultural heritage. Good lighting is essential to provide pictures with clear visibility of details and content, but it is a challenging task. Indeed, illuminating a site may require complex infrastructures, while uncontrolled lights may damage the artifacts. In this framework, computer vision techniques may greatly help archeology by relighting and/or improving the images of archaeological objects that cannot be acquired under a good light. This work presents MEEK, a basic tool to improve low-light, back-light and spot-light images, increasing the visibility of their details and content, while mitigating undesired effects due to illumination. MEEK embeds three algorithms: the Retinex inspired image enhancer SuPeR, the backlight and spotlight image relighting method REK, and the popular contrast enhancer CLAHE. One or more of these algorithms can be applied to the input image, depending on the light conditions of the acquired environments as well as on the final task for which the image is used. Here, MEEK is tested on many archaeological color pictures with bad light showing good performance. The code of MEEK is freely available at https://github.com/MichelaLecca/MEEK.

Paper Citation

in Harvard Style

Lecca M. (2023). A Basic Tool for Improving Bad Illuminated Archaeological Pictures. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP; ISBN 978-989-758-634-7, SciTePress, pages 204-211. DOI: 10.5220/0011648800003417

in Bibtex Style

@conference{visapp23,
author={Michela Lecca},
title={A Basic Tool for Improving Bad Illuminated Archaeological Pictures},
booktitle={Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP},
year={2023},
pages={204-211},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011648800003417},
isbn={978-989-758-634-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP
TI - A Basic Tool for Improving Bad Illuminated Archaeological Pictures
SN - 978-989-758-634-7
AU - Lecca M.
PY - 2023
SP - 204
EP - 211
DO - 10.5220/0011648800003417
PB - SciTePress