Underwater Image Enhancement by the Retinex Inspired Contrast Enhancer STRESS

Michela Lecca

2022

Abstract

Underwater images are often affected by undesired effects, like noise, color casts and poor detail visibility, hampering the understanding of the image content. This work proposes to improve the quality of such images by means of STRESS, a Retinex inspired contrast enhancer originally designed to process general, real-world pictures. STRESS, which is based on a local color spatial processing inspired to the human vision mechanism, is here tested and compared with other approaches on the public underwater image dataset UIEB. The experiments show that in general STRESS remarkably increases the quality of the input image, while preserving its local structure. The images enhanced by STRESS are released for free to enable visual inspection, further analysis and comparisons.

Paper Citation

in Harvard Style

Lecca M. (2022). Underwater Image Enhancement by the Retinex Inspired Contrast Enhancer STRESS. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP; ISBN 978-989-758-555-5, SciTePress, pages 627-634. DOI: 10.5220/0010895700003124

in Bibtex Style

@conference{visapp22,
author={Michela Lecca},
title={Underwater Image Enhancement by the Retinex Inspired Contrast Enhancer STRESS},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP},
year={2022},
pages={627-634},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010895700003124},
isbn={978-989-758-555-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 4: VISAPP
TI - Underwater Image Enhancement by the Retinex Inspired Contrast Enhancer STRESS
SN - 978-989-758-555-5
AU - Lecca M.
PY - 2022
SP - 627
EP - 634
DO - 10.5220/0010895700003124
PB - SciTePress