Enhancement of Degraded Images by Natural Phenomena

Daily Daleno de O. Rodrigues, Anderson G. Fontoura, José R. Hughes Carvalho, José P. de Queiroz Neto, Renato P. Vieira

2015

Abstract

The efficiency of environmental monitoring through imagery data is strongly dependent on the quality of the acquired information, despite weather conditions or other uncontrolled degradation factor. This article describes a series of combined techniques of image enhancement to partially recover information “lost” due to unfavorable operational conditions or natural phenomena, such as: fog, rainstorms, underwater dust (green dust), poor illumination, etc. We based our approach on a process known as homomorphic filtering, which is intrinsically related to the transformation from the spatial to the frequency domains, directly involving the Fourier Transforms, followed by specific enhancement techniques, such as Clipping and Stretching. Although, the use of these techniques separately, without the proper adaptation and coupling, can result in damaging even more the image, the authors developed an efficient sequence of enhanced filtering able to recover most of the affected information. Moreover, the proposed methodology proved to be generally applicable to a large class of images in poor conditions, with a performance comparable to the methodology used as benchmarks.

Paper Citation

in Harvard Style

Daleno de O. Rodrigues D., G. Fontoura A., R. Hughes Carvalho J., P. de Queiroz Neto J. and P. Vieira R. (2015). Enhancement of Degraded Images by Natural Phenomena . In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-089-5, pages 54-61. DOI: 10.5220/0005266500540061

in Bibtex Style

@conference{visapp15,
author={Daily Daleno de O. Rodrigues and Anderson G. Fontoura and José R. Hughes Carvalho and José P. de Queiroz Neto and Renato P. Vieira},
title={Enhancement of Degraded Images by Natural Phenomena},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={54-61},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005266500540061},
isbn={978-989-758-089-5},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2015)
TI - Enhancement of Degraded Images by Natural Phenomena
SN - 978-989-758-089-5
AU - Daleno de O. Rodrigues D.
AU - G. Fontoura A.
AU - R. Hughes Carvalho J.
AU - P. de Queiroz Neto J.
AU - P. Vieira R.
PY - 2015
SP - 54
EP - 61
DO - 10.5220/0005266500540061