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Blind Haze Separation
Abstract
Outdoor imaging is plagued by poor visibility conditions due to atmospheric scattering, particularly in haze. A major problem is spatially-varying reduction of contrast by stray radiance (airlight), which is scattered by the haze particles towards the camera. Recent computer vision methods have shown that images can be compensated for haze, and even yield a depth map of the scene. A key step in such a scene recovery is subtraction of the airlight. In particular, this can be achieved by analyzing polarization-filtered images. However, the recovery requires parameters of the airlight. These parameters were estimated in past studies by measuring pixels in sky areas. This paper derives an approach for blindly recovering the parameter needed for separating the airlight from the measurements, thus recovering contrast, with neither user interaction nor existence of the sky in the frame. This eases the interaction and conditions needed for image dehazing, which also requires compensation for attenuation. The approach has proved successful in experiments, some of which are shown here.
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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
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
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
DRCDN: learning deep residual convolutional dehazing networks
Zhang, S., & He, F. (2020) · The Visual Computer · doi:10.1007/s00371-019-01774-8 · Cited by 158
Metadata
- Authors
- Shwartz, S., Namer, E., & Schechner, Y. Y.
- Venue
- 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06)
- Publisher
- IEEE
- Published
- 2006-07-10
- Volume
- 2
- Pages
- 1984-1991
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2141030717
- Cited by
- 512
- References
- 0
- FWCI
- 6.79
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Shwartz, S., Namer, E., & Schechner, Y. Y. (2006). Blind Haze Separation. 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06). https://doi.org/10.1109/cvpr.2006.71
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