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
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
SUN database: Large-scale scene recognition from abbey to zoo
Xiao, J., Hays, J., Ehinger, K. A., Oliva, A., & Torralba, A. (2010) · 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2010.5539970 · Cited by 3,283
Cited by
An Underwater Image Enhancement Benchmark Dataset and Beyond
Li, C., Guo, C., Ren, W., Cong, R., Hou, J., Kwong, S., & Tao, D. (2020) · IEEE Transactions on Image Processing · doi:10.1109/tip.2019.2955241 · Cited by 2,373
Color balance and fusion for underwater image enhancement
Ancuti, C. O., Ancuti, C., De Vleeschouwer, C., & Bekaert, P. (2018) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2759252 · Cited by 1,357
Underwater scene prior inspired deep underwater image and video enhancement
Li, C., Anwar, S., & Porikli, F. (2020) · Pattern Recognition · doi:10.1016/j.patcog.2019.107038 · Cited by 1,252
U-Shape Transformer for Underwater Image Enhancement
Peng, L., Zhu, C., & Bian, L. (2023) · IEEE Transactions on Image Processing · doi:10.1109/tip.2023.3276332 · Cited by 912
Underwater Image Enhancement via Minimal Color Loss and Locally Adaptive Contrast Enhancement
Zhang, W., Zhuang, P., Sun, H.-H., Li, G., Kwong, S., & Li, C. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3177129 · Cited by 888
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.