Clear underwater vision

By Yoav Y. Schechner, Nir Karpel. Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004., 2004

400 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/f7d44d973439d7844b236f4225881f057699dfd4

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Citations in the corpus

Underwater Single Image Color Restoration Using Haze-Lines and a New Quantitative Dataset (2018, background): “E.g., Schechner and Karpel [4], [5] take two images with orthogonal polarizer angles and utilize the partial polarization of light to restore the visibility.”
Underwater Image Enhancement Using an Integrated Colour Model (2007, unknown): “Yoav [12] have used a Physics-based model.”
Underwater Image Enhancement via Medium Transmission-Guided Multi-Color Space Embedding (2021, methodology): “In addition to extra information [20], [21] and specialized hardware devices [22], underwater image enhancement can be roughly classiﬁed into two groups: traditional methods and deep learning-based methods.”
Underwater Image Enhancement by Dehazing With Minimum Information Loss and Histogram Distribution Prior (2016, unknown): “(a) Underwater images captured under challenging scenes, from left to right: turbid scene [19], deep water scene (26 meters depths) [35], artificial lighting scene [44], low-light scene (image obtained from the Internet), and noise scene (adding gaussian random noise of zero mean noise with 0.01…”
Visibility in bad weather from a single image (2008, methodology): “Finally, we also intend to apply the proposed method to improve under-water visibility [9] or other turbid media that have the same optical model.”
Enhancing the low quality images using Unsupervised Colour Correction Method (2010, background): “The issue of backscatter can also be addressed using polarised filters [14].”
Automatic Red-Channel underwater image restoration (2015, methodology): “(6), (8), (10), (12), and the edge maps computed by the evaluation metric we are using are given in (7), (9), (11), (13).”
A Revised Underwater Image Formation Model (2018, background): “Authors in [35] showed quantitatively that F ⌧ D, and it does not contribute significantly to the degradation of an image.”
Active Polarization Descattering (2009, methodology): “Some recovered visibility as well as the 3D structure in haze and underwater [38], [39], [40] under distant natural illumination.”
Blind Haze Separation (2006, background): “Moreover, research into atmospheric imaging promotes other domains of vision through scattering media, such as water [9, 11, 14, 23, 24, 31] and tissue.”
Underwater image dehazing using joint trilateral filter (2014, unknown): “1), which is slightly modified by Schechner’ underwater imaging model [9].”
Recovery of underwater visibility and structure by polarization analysis (2005, background): “Partial preliminary results were presented in [34].”