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Chromatic framework for vision in bad weather
Abstract
Conventional vision systems are designed to perform in clear weather. However, any outdoor vision system is incomplete without mechanisms that guarantee satisfactory performance under poor weather conditions. It is known that the atmosphere can significantly alter light energy reaching an observer. Therefore, atmospheric scattering models must be used to make vision systems robust in bad weather. In this paper, we develop a geometric framework for analyzing the chromatic effects of atmospheric scattering. First, we study a simple color model for atmospheric scattering and verify it for fog and haze. Then, based on the physics of scattering, we derive several geometric constraints on scene color changes, caused by varying atmospheric conditions. Finally, using these constraints we develop algorithms for computing fog or haze color depth segmentation, extracting three dimensional structure, and recovering "true" scene colors, from two or more images taken under different but unknown weather conditions.
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Citations
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
Fattal, R. (2008) · ACM Transactions on Graphics · doi:10.1145/1360612.1360671 · Cited by 2,114
Contrast restoration of weather degraded images
Narasimhan, S. G., & Nayar, S. K. (2003) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2003.1201821 · Cited by 1,642
Self-citationBerman, 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
Fast Image Dehazing Method Based on Linear Transformation
Wang, W., Yuan, X., Wu, X., & Liu, Y. (2017) · IEEE Transactions on Multimedia · doi:10.1109/tmm.2017.2652069 · Cited by 319
Metadata
- Authors
- Narasimhan, S. G., & Nayar, S. K.
- Venue
- Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662)
- Publisher
- IEEE Comput. Soc
- Published
- 2002-11-07
- Volume
- 1
- Pages
- 598-605
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2109616376
- Cited by
- 786
- References
- 0
- FWCI
- 2.82
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Narasimhan, S. G., & Nayar, S. K. (2002). Chromatic framework for vision in bad weather. Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662). https://doi.org/10.1109/cvpr.2000.855874
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