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Cited by 739

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Underwater Depth Estimation and Image Restoration Based on Single Images

Drews, Paulo L.J., Nascimento, Erickson R., Botelho, Silvia S.C., Montenegro Campos, Mario Fernando·2016·IEEE Computer Graphics and Applications

Abstract

In underwater environments, the scattering and absorption phenomena affect the propagation of light, degrading the quality of captured images. In this work, the authors present a method based on a physical model of light propagation that takes into account the most significant effects to image degradation: absorption, scattering, and backscattering. The proposed method uses statistical priors to restore the visual quality of the images acquired in typical underwater scenarios.

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Metadata

Authors
Drews, P. L. J., Nascimento, E. R., Botelho, S. S. C., & Montenegro Campos, M. F.
Venue
IEEE Computer Graphics and Applications
Published
2016-03
Volume
36
Issue
2
Pages
24-35
ISSN
  • 0272-1716 (ISSN-L)
  • 1558-1756
OpenAlex
W2293581118
Cited by
739
References
1
FWCI
13.92
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Underwater Depth Estimation and Image Restoration Based on Single Images. https://app.cochat.ai/papers/10.1109/mcg.2016.26
The paper
Drews, P. L. J., Nascimento, E. R., Botelho, S. S. C., & Montenegro Campos, M. F. (2016). Underwater Depth Estimation and Image Restoration Based on Single Images. IEEE Computer Graphics and Applications. https://doi.org/10.1109/mcg.2016.26

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.