Locally Adaptive Color Correction for Underwater Dehazing and Image Matching
(2017) IEEE Conference on Computer Vision and Pattern Recognition, New Trends in Image Restoration and Enhancement Workshop — Location: Honolulu, HI, USA (21.July.2017)
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- Abstract
- Underwater images are known to be strongly deteriorated by a combination of wavelength-dependent light attenuation and scattering. This results in complex color casts that depend both on the scene depth map and on the light spectrum. Color transfer, which is a technique of choice to counterbalance color casts, assumes stationary casts, defined by global parameters, and is therefore not directly applicable to the locally variable color casts encountered in underwater scenarios. To fill this gap, this paper introduces an original fusion-based strategy to exploit color transfer while tuning the color correction locally, as a function of the light attenuation level estimated from the red channel. The Dark Channel Prior (DCP) is then used to restore the color compensated image, by inverting the simplified Koschmieder light transmission model, as for outdoor dehazing. Our technique enhances image contrast in a quite effective manner and also supports accurate transmission map estimation. Our extensive experiments also show that our color correction strongly improves the effectiveness of local keypoints matching.
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Citations
Ancuti, C., Ancuti, C., De Vleeschouwer, C., & Garcia, R. (2017). Locally Adaptive Color Correction for Underwater Dehazing and Image Matching. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Workshops 2017. Published. IEEE Conference on Computer Vision and Pattern Recognition, New Trends in Image Restoration and Enhancement Workshop, Honolulu, HI, USA. https://doi.org/10.1109/CVPRW.2017.136