The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Single image dehazing
Abstract
In this paper we present a new method for estimating the optical transmission in hazy scenes given a single input image. Based on this estimation, the scattered light is eliminated to increase scene visibility and recover haze-free scene contrasts. In this new approach we formulate a refined image formation model that accounts for surface shading in addition to the transmission function. This allows us to resolve ambiguities in the data by searching for a solution in which the resulting shading and transmission functions are locally statistically uncorrelated. A similar principle is used to estimate the color of the haze. Results demonstrate the new method abilities to remove the haze layer as well as provide a reliable transmission estimate which can be used for additional applications such as image refocusing and novel view synthesis.
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
Independent component analysis: algorithms and applications
Hyvärinen, A., & Oja, E. (2000) · Neural Networks · doi:10.1016/s0893-6080(00)00026-5 · Cited by 8,705
Recovering high dynamic range radiance maps from photographs
Debevec, P. E., & Malik, J. (2008) · ACM SIGGRAPH 2008 classes · doi:10.1145/1401132.1401174 · Cited by 2,399
Visibility in bad weather from a single image
Tan, R. T. (2008) · 2008 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2008.4587643 · Cited by 2,280
Chavez, P. S. (1988) · Remote Sensing of Environment · doi:10.1016/0034-4257(88)90019-3 · Cited by 1,825
Recovering high dynamic range radiance maps from photographs
Debevec, P. E., & Malik, J. (1997) · Proceedings of the 24th annual conference on Computer graphics and interactive techniques - SIGGRAPH '97 · doi:10.1145/258734.258884 · Cited by 1,775
Evaluation of Cost Functions for Stereo Matching
Hirschmuller, H., & Scharstein, D. (2007) · 2007 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2007.383248 · Cited by 1,122
Image and depth from a conventional camera with a coded aperture
Levin, A., Fergus, R., Durand, F., & Freeman, W. T. (2007) · ACM SIGGRAPH 2007 papers · doi:10.1145/1275808.1276464 · Cited by 1,023
Image and depth from a conventional camera with a coded aperture
Levin, A., Fergus, R., Durand, F., & Freeman, W. T. (2007) · ACM Transactions on Graphics · doi:10.1145/1276377.1276464 · Cited by 980
Nayar, S. K., & Narasimhan, S. G. (1999) · Proceedings of the Seventh IEEE International Conference on Computer Vision · doi:10.1109/iccv.1999.790306 · Cited by 883
Instant dehazing of images using polarization
Schechner, Y. Y., Narasimhan, S. G., & Nayar, S. K. (2005) · Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001 · doi:10.1109/cvpr.2001.990493 · Cited by 859
Cited by
Single image haze removal using dark channel prior
He, K., Sun, J., & Tang, X. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2010.168 · Cited by 7,601
DehazeNet: An End-to-End System for Single Image Haze Removal
Cai, B., Xu, X., Jia, K., Qing, C., & Tao, D. (2016) · IEEE Transactions on Image Processing · doi:10.1109/tip.2016.2598681 · Cited by 3,367
Berman, D., Treibitz, T., & Avidan, S. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.185 · Cited by 1,642
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
Fast visibility restoration from a single color or gray level image
Tarel, J.-P., & Hautiere, N. (2009) · 2009 IEEE 12th International Conference on Computer Vision · doi:10.1109/iccv.2009.5459251 · Cited by 1,313
Metadata
- Authors
- Fattal, R.
- Venue
- ACM Transactions on Graphics
- Published
- 2008-08
- Volume
- 27
- Issue
- 3
- Pages
- 1-9
- ISSN
- 0730-0301 (ISSN-L)
- 1557-7368
- OpenAlex
- W2028990532
- Cited by
- 2,114
- References
- 31
- FWCI
- 55.84
- 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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Single image dehazing. https://app.cochat.ai/papers/10.1145/1360612.1360671
- The paper
- Fattal, R. (2008). Single image dehazing. ACM Transactions on Graphics. https://doi.org/10.1145/1360612.1360671
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.
