Abstract

Object identification in highly turbid optical media depends mainly on the quality of collected images. Underwater images acquired in a turbid environment are generally of very poor quality. Attenuation and backscattering of light by water, by materials dissolved in the water, and by particulate material are the main causes of the degradation of underwater images. It is therefore essential to improve the quality of such images to facilitate object identification. The focus of this paper is to report the principle and validation of a fast and effective method of improving the quality of underwater images. On the one hand, this method uses a polarimetric imaging optical system to reduce the effect of diffusion on the image acquisition. On the other hand, it is based on an optimized version of the dark channel prior (DCP) method that has received a great deal of attention for image dehazing. Results derived from images obtained in a controlled laboratory water tank environment with different turbidity conditions and images from tests using the proposed method at sea demonstrate an ability to significantly improve visibility and reduce runtime by a factor of about 50 for a 4K image when compared to conventional DCP methods.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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H. Lu, Y. Li, Y. Zhang, M. Chen, S. Serikawa, and H. Kim, “Underwater optical image processing: a comprehensive review,” Mob. Netw. Appl. 22(6), 1204–1211 (2017).
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2016 (3)

S. Lee, S. Yun, J.-H. Nam, C. S. Won, and S.-W. Jung, “A review on dark channel prior based image dehazing algorithms,” EURASIP J. Image Video Process. 2016(1), 4 (2016).
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S. S. Sankpal and S. S. Deshpande, “A review on image enhancement and color correction techniques for underwater images,” Advances in Computational Sciences and Technology 9(1), 11–23 (2016).

K. Panetta, C. Gao, and S. Agaian, “Human-visual-system-inspired underwater image quality measures,” IEEE J. Oceanic Eng. 41(3), 541–551 (2016).
[Crossref]

2015 (3)

A. Shahrizan, A. Ghani, N. Ashidi, and M. Isa, “Underwater image quality enhancement through integrated color model with Rayleigh distribution,” Appl. Soft Comput. J 27, 219–230 (2015).
[Crossref]

J. V. C. I. R. A. Galdran, D. Pardo, A. Picón, and A. Alvarez-gila, “Automatic red-channel underwater image restoration,” J. Vis. Commun. Image Represent. 26, 132–145 (2015).
[Crossref]

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[Crossref] [PubMed]

2013 (3)

2012 (1)

B. Ouyang, F. R. Dalgleish, F. M. Caimi, A. K. Vuorenkoski, T. E. Giddings, and J. J. Shirron, “Image enhancement for underwater pulsed laser line scan imaging system,” International Society for Optics and Photonics 8372, 83720R (2012).
[Crossref]

2011 (1)

K. He, J. Sun, and X. Tang, “Single image haze removal using dark channel prior,” IEEE Trans. Pattern Anal. Mach. Intell. 33(12), 2341–2353 (2011).
[Crossref] [PubMed]

2010 (1)

R. Schettini and S. Corchs, “Underwater Image Processing : State of the art of restoration and image enhancement methods,” EURASIP J. Adv. Signal Process. 2010(1), 14 (2010).

2009 (2)

2006 (3)

E. Trucco and A. T. Olmos-Antillon, “Self-tuning underwater image restoration,” IEEE J. Oceanic Eng. 31(2), 511–519 (2006).
[Crossref]

S. Bazeille, I. Quidu, L. Jaulin, and J.-P. Malkasse, “Automatic underwater image pre-processing,” Cmm 06(1), xx (2006).

J. S. Tyo, D. L. Goldstein, D. B. Chenault, and J. A. Shaw, “Review of passive imaging polarimetry for remote sensing applications,” Appl. Opt. 45(22), 5453–5469 (2006).
[Crossref] [PubMed]

2005 (2)

2003 (1)

M. Legris, K. Lebart, F. Fohanno, and B. Zerr, “Les capteurs d’imagerie en robotique sous-marine : tendances actuelles et futures,” Trait. du Signal 20, 137–164 (2003).

2002 (1)

R. Garcia, T. Nicosevici, and X. Cufi, “On the way to solve lighting problems in underwater Imaging,” In Oceans'02 MTS/IEEE 2, 1018–1024 (2002).

2000 (1)

1999 (2)

1998 (1)

1994 (1)

D. Bicout, C. Brosseau, A. S. Martinez, and J. M. Schmitt, “Depolarization of multiply scattered waves by spherical diffusers: Influence of the size parameter,” Phys. Rev. E Stat. Phys. Plasmas Fluids Relat. Interdiscip. Topics 49(2), 1767–1770 (1994).
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1990 (1)

J. S. Jaffe, “Computer modeling and the design of optimal underwater imaging systems,” IEEE J. Oceanic Eng. 15(2), 101–111 (1990).
[Crossref]

1989 (1)

F. C. MacKintosh, J. X. Zhu, D. J. Pine, and D. A. Weitz, “Polarization memory of multiply scattered light,” Phys. Rev. B Condens. Matter 40(13), 9342–9345 (1989).
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1984 (1)

1980 (1)

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1974 (1)

A. Morel, “Optical properties of pure water and pure sea water,” Opt. Asp. Oceanogr 1(1), 1–24 (1974).

1967 (1)

Agaian, S.

K. Panetta, C. Gao, and S. Agaian, “Human-visual-system-inspired underwater image quality measures,” IEEE J. Oceanic Eng. 41(3), 541–551 (2016).
[Crossref]

Alfalou, A.

Alvarez-gila, A.

J. V. C. I. R. A. Galdran, D. Pardo, A. Picón, and A. Alvarez-gila, “Automatic red-channel underwater image restoration,” J. Vis. Commun. Image Represent. 26, 132–145 (2015).
[Crossref]

Ancuti, C.

C. Ancuti, C. O. Ancuti, T. Haber, and P. Bekaert, “Enhancing underwater images and videos by fusion,” IEEE Conference on Computer Vision and Pattern Recognition. 81–88 (2012).
[Crossref]

Ancuti, C. O.

C. Ancuti, C. O. Ancuti, T. Haber, and P. Bekaert, “Enhancing underwater images and videos by fusion,” IEEE Conference on Computer Vision and Pattern Recognition. 81–88 (2012).
[Crossref]

Ashidi, N.

A. Shahrizan, A. Ghani, N. Ashidi, and M. Isa, “Underwater image quality enhancement through integrated color model with Rayleigh distribution,” Appl. Soft Comput. J 27, 219–230 (2015).
[Crossref]

Bazeille, S.

S. Bazeille, I. Quidu, L. Jaulin, and J.-P. Malkasse, “Automatic underwater image pre-processing,” Cmm 06(1), xx (2006).

Bekaert, P.

C. Ancuti, C. O. Ancuti, T. Haber, and P. Bekaert, “Enhancing underwater images and videos by fusion,” IEEE Conference on Computer Vision and Pattern Recognition. 81–88 (2012).
[Crossref]

Bergmann, F.

Bicout, D.

D. Bicout, C. Brosseau, A. S. Martinez, and J. M. Schmitt, “Depolarization of multiply scattered waves by spherical diffusers: Influence of the size parameter,” Phys. Rev. E Stat. Phys. Plasmas Fluids Relat. Interdiscip. Topics 49(2), 1767–1770 (1994).
[Crossref] [PubMed]

Boulvert, F.

Brennan, M. J.

Brosseau, C.

Caimi, F. M.

B. Ouyang, F. R. Dalgleish, F. M. Caimi, A. K. Vuorenkoski, T. E. Giddings, and J. J. Shirron, “Image enhancement for underwater pulsed laser line scan imaging system,” International Society for Optics and Photonics 8372, 83720R (2012).
[Crossref]

Cariou, J.

Chang, P. C.

Chen, M.

H. Lu, Y. Li, Y. Zhang, M. Chen, S. Serikawa, and H. Kim, “Underwater optical image processing: a comprehensive review,” Mob. Netw. Appl. 22(6), 1204–1211 (2017).
[Crossref]

H. Lu, Y. Li, Y. Zhang, M. Chen, S. Serikawa, and H. Kim, “Underwater optical image Processing : a comprehensive review,” Mob. Netw. Appl. 22(6), 1204–1211 (2017).
[Crossref]

Chenault, D. B.

Cochenour, B.

Corchs, S.

R. Schettini and S. Corchs, “Underwater Image Processing : State of the art of restoration and image enhancement methods,” EURASIP J. Adv. Signal Process. 2010(1), 14 (2010).

Cufi, X.

R. Garcia, T. Nicosevici, and X. Cufi, “On the way to solve lighting problems in underwater Imaging,” In Oceans'02 MTS/IEEE 2, 1018–1024 (2002).

Dalgleish, F. R.

B. Ouyang, F. R. Dalgleish, F. M. Caimi, A. K. Vuorenkoski, T. E. Giddings, and J. J. Shirron, “Image enhancement for underwater pulsed laser line scan imaging system,” International Society for Optics and Photonics 8372, 83720R (2012).
[Crossref]

Delrot, P.

Dereniak, E. L.

Deshpande, S. S.

S. S. Sankpal and S. S. Deshpande, “A review on image enhancement and color correction techniques for underwater images,” Advances in Computational Sciences and Technology 9(1), 11–23 (2016).

Dogariu, A.

Dubreuil, M.

Fohanno, F.

M. Legris, K. Lebart, F. Fohanno, and B. Zerr, “Les capteurs d’imagerie en robotique sous-marine : tendances actuelles et futures,” Trait. du Signal 20, 137–164 (2003).

Foschum, F.

Fry, E. S.

Galdran, J. V. C. I. R. A.

J. V. C. I. R. A. Galdran, D. Pardo, A. Picón, and A. Alvarez-gila, “Automatic red-channel underwater image restoration,” J. Vis. Commun. Image Represent. 26, 132–145 (2015).
[Crossref]

Gao, C.

K. Panetta, C. Gao, and S. Agaian, “Human-visual-system-inspired underwater image quality measures,” IEEE J. Oceanic Eng. 41(3), 541–551 (2016).
[Crossref]

Garcia, R.

R. Garcia, T. Nicosevici, and X. Cufi, “On the way to solve lighting problems in underwater Imaging,” In Oceans'02 MTS/IEEE 2, 1018–1024 (2002).

Ghani, A.

A. Shahrizan, A. Ghani, N. Ashidi, and M. Isa, “Underwater image quality enhancement through integrated color model with Rayleigh distribution,” Appl. Soft Comput. J 27, 219–230 (2015).
[Crossref]

Giddings, T. E.

B. Ouyang, F. R. Dalgleish, F. M. Caimi, A. K. Vuorenkoski, T. E. Giddings, and J. J. Shirron, “Image enhancement for underwater pulsed laser line scan imaging system,” International Society for Optics and Photonics 8372, 83720R (2012).
[Crossref]

Gilbert, G. D.

Goldstein, D. L.

Guern, Y.

Haber, T.

C. Ancuti, C. O. Ancuti, T. Haber, and P. Bekaert, “Enhancing underwater images and videos by fusion,” IEEE Conference on Computer Vision and Pattern Recognition. 81–88 (2012).
[Crossref]

He, K.

K. He, J. Sun, and X. Tang, “Single image haze removal using dark channel prior,” IEEE Trans. Pattern Anal. Mach. Intell. 33(12), 2341–2353 (2011).
[Crossref] [PubMed]

Hohmann, A.

Hopcraft, K. I.

Isa, M.

A. Shahrizan, A. Ghani, N. Ashidi, and M. Isa, “Underwater image quality enhancement through integrated color model with Rayleigh distribution,” Appl. Soft Comput. J 27, 219–230 (2015).
[Crossref]

Jaffe, J. S.

J. S. Jaffe, “Computer modeling and the design of optimal underwater imaging systems,” IEEE J. Oceanic Eng. 15(2), 101–111 (1990).
[Crossref]

Jang, W. D.

J. H. Kim, W. D. Jang, J. Y. Sim, and C. S. Kim, “Optimized contrast enhancement for real-time image and video dehazing,” J. Vis. Commun. Image Represent. 24(3), 410–425 (2013).
[Crossref]

Jaulin, L.

S. Bazeille, I. Quidu, L. Jaulin, and J.-P. Malkasse, “Automatic underwater image pre-processing,” Cmm 06(1), xx (2006).

Jordan, D. L.

Jung, S.-W.

S. Lee, S. Yun, J.-H. Nam, C. S. Won, and S.-W. Jung, “A review on dark channel prior based image dehazing algorithms,” EURASIP J. Image Video Process. 2016(1), 4 (2016).
[Crossref]

Karpel, N.

Y. Y. Schechner and N. Karpel, “Recovery of underwater visibility and structure by polarization analysis,” IEEE J. Oceanic Eng. 30(3), 570–587 (2005).
[Crossref]

Kattawar, G. W.

Kemme, S. A.

Kienle, A.

Kim, C. S.

J. H. Kim, W. D. Jang, J. Y. Sim, and C. S. Kim, “Optimized contrast enhancement for real-time image and video dehazing,” J. Vis. Commun. Image Represent. 24(3), 410–425 (2013).
[Crossref]

Kim, H.

H. Lu, Y. Li, Y. Zhang, M. Chen, S. Serikawa, and H. Kim, “Underwater optical image processing: a comprehensive review,” Mob. Netw. Appl. 22(6), 1204–1211 (2017).
[Crossref]

H. Lu, Y. Li, Y. Zhang, M. Chen, S. Serikawa, and H. Kim, “Underwater optical image Processing : a comprehensive review,” Mob. Netw. Appl. 22(6), 1204–1211 (2017).
[Crossref]

Kim, J. H.

J. H. Kim, W. D. Jang, J. Y. Sim, and C. S. Kim, “Optimized contrast enhancement for real-time image and video dehazing,” J. Vis. Commun. Image Represent. 24(3), 410–425 (2013).
[Crossref]

Kouzoubov, A.

Krauter, P.

Le Brun, G.

Le Jeune, B.

Lebart, K.

M. Legris, K. Lebart, F. Fohanno, and B. Zerr, “Les capteurs d’imagerie en robotique sous-marine : tendances actuelles et futures,” Trait. du Signal 20, 137–164 (2003).

Lee, S.

S. Lee, S. Yun, J.-H. Nam, C. S. Won, and S.-W. Jung, “A review on dark channel prior based image dehazing algorithms,” EURASIP J. Image Video Process. 2016(1), 4 (2016).
[Crossref]

Legris, M.

M. Legris, K. Lebart, F. Fohanno, and B. Zerr, “Les capteurs d’imagerie en robotique sous-marine : tendances actuelles et futures,” Trait. du Signal 20, 137–164 (2003).

Leonard, I.

Lewis, G. D.

Li, Y.

H. Lu, Y. Li, Y. Zhang, M. Chen, S. Serikawa, and H. Kim, “Underwater optical image processing: a comprehensive review,” Mob. Netw. Appl. 22(6), 1204–1211 (2017).
[Crossref]

H. Lu, Y. Li, Y. Zhang, M. Chen, S. Serikawa, and H. Kim, “Underwater optical image Processing : a comprehensive review,” Mob. Netw. Appl. 22(6), 1204–1211 (2017).
[Crossref]

Lu, H.

H. Lu, Y. Li, Y. Zhang, M. Chen, S. Serikawa, and H. Kim, “Underwater optical image processing: a comprehensive review,” Mob. Netw. Appl. 22(6), 1204–1211 (2017).
[Crossref]

H. Lu, Y. Li, Y. Zhang, M. Chen, S. Serikawa, and H. Kim, “Underwater optical image Processing : a comprehensive review,” Mob. Netw. Appl. 22(6), 1204–1211 (2017).
[Crossref]

MacKintosh, F. C.

F. C. MacKintosh, J. X. Zhu, D. J. Pine, and D. A. Weitz, “Polarization memory of multiply scattered light,” Phys. Rev. B Condens. Matter 40(13), 9342–9345 (1989).
[Crossref] [PubMed]

Mahon, R.

Malkasse, J.-P.

S. Bazeille, I. Quidu, L. Jaulin, and J.-P. Malkasse, “Automatic underwater image pre-processing,” Cmm 06(1), xx (2006).

Martinez, A. S.

D. Bicout, C. Brosseau, A. S. Martinez, and J. M. Schmitt, “Depolarization of multiply scattered waves by spherical diffusers: Influence of the size parameter,” Phys. Rev. E Stat. Phys. Plasmas Fluids Relat. Interdiscip. Topics 49(2), 1767–1770 (1994).
[Crossref] [PubMed]

McGlamery, B. L.

B. L. McGlamery, “A computer model for underwater camera systems,” International Society for Optics and Photonics, In Ocean Optics VI. 208, 221–231 (1980).
[Crossref]

Morel, A.

A. Morel, “Optical properties of pure water and pure sea water,” Opt. Asp. Oceanogr 1(1), 1–24 (1974).

Mullen, L.

Muth, J.

Nam, J.-H.

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E. Trucco and A. T. Olmos-Antillon, “Self-tuning underwater image restoration,” IEEE J. Oceanic Eng. 31(2), 511–519 (2006).
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B. Ouyang, F. R. Dalgleish, F. M. Caimi, A. K. Vuorenkoski, T. E. Giddings, and J. J. Shirron, “Image enhancement for underwater pulsed laser line scan imaging system,” International Society for Optics and Photonics 8372, 83720R (2012).
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Panetta, K.

K. Panetta, C. Gao, and S. Agaian, “Human-visual-system-inspired underwater image quality measures,” IEEE J. Oceanic Eng. 41(3), 541–551 (2016).
[Crossref]

Pardo, D.

J. V. C. I. R. A. Galdran, D. Pardo, A. Picón, and A. Alvarez-gila, “Automatic red-channel underwater image restoration,” J. Vis. Commun. Image Represent. 26, 132–145 (2015).
[Crossref]

Pernicka, J. C.

Picón, A.

J. V. C. I. R. A. Galdran, D. Pardo, A. Picón, and A. Alvarez-gila, “Automatic red-channel underwater image restoration,” J. Vis. Commun. Image Represent. 26, 132–145 (2015).
[Crossref]

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Pine, D. J.

F. C. MacKintosh, J. X. Zhu, D. J. Pine, and D. A. Weitz, “Polarization memory of multiply scattered light,” Phys. Rev. B Condens. Matter 40(13), 9342–9345 (1989).
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Rakovic, M. J.

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S. S. Sankpal and S. S. Deshpande, “A review on image enhancement and color correction techniques for underwater images,” Advances in Computational Sciences and Technology 9(1), 11–23 (2016).

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R. Schettini and S. Corchs, “Underwater Image Processing : State of the art of restoration and image enhancement methods,” EURASIP J. Adv. Signal Process. 2010(1), 14 (2010).

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D. Bicout, C. Brosseau, A. S. Martinez, and J. M. Schmitt, “Depolarization of multiply scattered waves by spherical diffusers: Influence of the size parameter,” Phys. Rev. E Stat. Phys. Plasmas Fluids Relat. Interdiscip. Topics 49(2), 1767–1770 (1994).
[Crossref] [PubMed]

Scrymgeour, D. A.

Serikawa, S.

H. Lu, Y. Li, Y. Zhang, M. Chen, S. Serikawa, and H. Kim, “Underwater optical image Processing : a comprehensive review,” Mob. Netw. Appl. 22(6), 1204–1211 (2017).
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H. Lu, Y. Li, Y. Zhang, M. Chen, S. Serikawa, and H. Kim, “Underwater optical image processing: a comprehensive review,” Mob. Netw. Appl. 22(6), 1204–1211 (2017).
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A. Shahrizan, A. Ghani, N. Ashidi, and M. Isa, “Underwater image quality enhancement through integrated color model with Rayleigh distribution,” Appl. Soft Comput. J 27, 219–230 (2015).
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Shaw, J. A.

Shirron, J. J.

B. Ouyang, F. R. Dalgleish, F. M. Caimi, A. K. Vuorenkoski, T. E. Giddings, and J. J. Shirron, “Image enhancement for underwater pulsed laser line scan imaging system,” International Society for Optics and Photonics 8372, 83720R (2012).
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J. H. Kim, W. D. Jang, J. Y. Sim, and C. S. Kim, “Optimized contrast enhancement for real-time image and video dehazing,” J. Vis. Commun. Image Represent. 24(3), 410–425 (2013).
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E. Trucco and A. T. Olmos-Antillon, “Self-tuning underwater image restoration,” IEEE J. Oceanic Eng. 31(2), 511–519 (2006).
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S. Lee, S. Yun, J.-H. Nam, C. S. Won, and S.-W. Jung, “A review on dark channel prior based image dehazing algorithms,” EURASIP J. Image Video Process. 2016(1), 4 (2016).
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S. Lee, S. Yun, J.-H. Nam, C. S. Won, and S.-W. Jung, “A review on dark channel prior based image dehazing algorithms,” EURASIP J. Image Video Process. 2016(1), 4 (2016).
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S. S. Sankpal and S. S. Deshpande, “A review on image enhancement and color correction techniques for underwater images,” Advances in Computational Sciences and Technology 9(1), 11–23 (2016).

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A. Shahrizan, A. Ghani, N. Ashidi, and M. Isa, “Underwater image quality enhancement through integrated color model with Rayleigh distribution,” Appl. Soft Comput. J 27, 219–230 (2015).
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Appl. Spectrosc. (1)

Cmm (1)

S. Bazeille, I. Quidu, L. Jaulin, and J.-P. Malkasse, “Automatic underwater image pre-processing,” Cmm 06(1), xx (2006).

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R. Schettini and S. Corchs, “Underwater Image Processing : State of the art of restoration and image enhancement methods,” EURASIP J. Adv. Signal Process. 2010(1), 14 (2010).

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S. Lee, S. Yun, J.-H. Nam, C. S. Won, and S.-W. Jung, “A review on dark channel prior based image dehazing algorithms,” EURASIP J. Image Video Process. 2016(1), 4 (2016).
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[Crossref]

K. Panetta, C. Gao, and S. Agaian, “Human-visual-system-inspired underwater image quality measures,” IEEE J. Oceanic Eng. 41(3), 541–551 (2016).
[Crossref]

IEEE Trans. Pattern Anal. Mach. Intell. (2)

T. Treibitz and Y. Y. Schechner, “Active polarization descattering,” IEEE Trans. Pattern Anal. Mach. Intell. 31(3), 385–399 (2009).
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K. He, J. Sun, and X. Tang, “Single image haze removal using dark channel prior,” IEEE Trans. Pattern Anal. Mach. Intell. 33(12), 2341–2353 (2011).
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R. Garcia, T. Nicosevici, and X. Cufi, “On the way to solve lighting problems in underwater Imaging,” In Oceans'02 MTS/IEEE 2, 1018–1024 (2002).

International Society for Optics and Photonics (1)

B. Ouyang, F. R. Dalgleish, F. M. Caimi, A. K. Vuorenkoski, T. E. Giddings, and J. J. Shirron, “Image enhancement for underwater pulsed laser line scan imaging system,” International Society for Optics and Photonics 8372, 83720R (2012).
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[Crossref]

J. H. Kim, W. D. Jang, J. Y. Sim, and C. S. Kim, “Optimized contrast enhancement for real-time image and video dehazing,” J. Vis. Commun. Image Represent. 24(3), 410–425 (2013).
[Crossref]

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H. Lu, Y. Li, Y. Zhang, M. Chen, S. Serikawa, and H. Kim, “Underwater optical image Processing : a comprehensive review,” Mob. Netw. Appl. 22(6), 1204–1211 (2017).
[Crossref]

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Phys. Rev. E Stat. Phys. Plasmas Fluids Relat. Interdiscip. Topics (1)

D. Bicout, C. Brosseau, A. S. Martinez, and J. M. Schmitt, “Depolarization of multiply scattered waves by spherical diffusers: Influence of the size parameter,” Phys. Rev. E Stat. Phys. Plasmas Fluids Relat. Interdiscip. Topics 49(2), 1767–1770 (1994).
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W. Hou, D. J. Gray, A. D. Weidemann, G. R. Fournier, and, J. L. Forand, “Automated underwater image restoration and retrieval of related optical properties,” IGARSS (2007).

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http://www.sealife-cameras.com/fr/cam%C3%A9ras/dc1400-pro-vid%C3%A9o

http://www.forssea-robotics.fr/html/produit.html

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Figures (16)

Fig. 1
Fig. 1 Absorption and scattering in water.
Fig. 2
Fig. 2 Experimental setup for underwater target detection. Pol1 is a linear polarizer, Pol2 is a linear analyzer, and S i denotes Stokes vector i.
Fig. 3
Fig. 3 (a) Light source and camera with polarizers. (b) The used experimental set-up based on polarization.
Fig. 4
Fig. 4 Images of the target for two different turbidity conditions (top row: μ s =0.056c m 1 , τ 0 =1.96), (bottom row μ s =0.084c m 1 , τ 0 =2.94). (a) and (d): unpolarized images; (b) and (e) parallel polarization images; (c) and (f). Cross-perpendicular polarization images.
Fig. 5
Fig. 5 (a) Water tank [3m × 2m], (b) FORSSEA Robotics waterproof imaging system, (c) polarization calibration, (d) polarimetric imaging system and marker in the water tank.
Fig. 6
Fig. 6 Image of marker for different turbidity conditions (from left to right: (a) clear water, (b) turbidity μ s1 ,(c) turbidity μ s2 ,(d) turbidity μ s3 .Top row: unpolarized images, bottom row: the corresponding cross linear polarization images.
Fig. 7
Fig. 7 Image of marker (capital letter P) at turbidity μ s2 . (a) Without polarization. (b) With cross linear polarization.
Fig. 8
Fig. 8 Principle of our algorithm for grayscale images.
Fig. 9
Fig. 9 Examples of image with different turbidity conditions: (a) target image in clear water, (b) target image in water tank with turbidity condition defined by μ s =0.056c m 1 , τ 0 =1.96, when skim milk is added, and (c) as in (b) with turbidity μ s =0.084c m 1 , τ 0 =2.94.
Fig. 10
Fig. 10 The top row of each image block shows a comparison of the recovered images when the input image is Fig. 9 (a): (b) using DCP, (c) using DCP with refinement of transmission map by soft matting, and (d) using our approach. The bottom row shows a comparison of the recovered images when the input image is Fig. 9(c).
Fig. 11
Fig. 11 (a) Input image. A comparison of transmission map between: (b) DCP and (c) our method.
Fig. 12
Fig. 12 Principle of our algorithm for color images.
Fig. 13
Fig. 13 The top row of each block of images shows a comparison of the recovered images when the input image is Fig. 9(a): (b) using DCP, (c) using DCP with refinement of transmission map by soft matting, and (d) using our approach. The bottom row shows a comparison of the recovered images when the input image is Fig. 9(c).
Fig. 14
Fig. 14 The top row of each block of images corresponds to turbidity condition ( μ s =0.056c m 1 , τ 0 =1.96): (a) target image acquired without polarization, (b) target image acquired with linear cross-polarization, and (c) target image acquired with linear.
Fig. 15
Fig. 15 Underwater imaging system.
Fig. 16
Fig. 16 Results at 8 meters deep in the port of Brest at night. (a) Images acquired without polarization, (b) images acquired with linear perpendicular-polarization, and (c) images acquired with linear perpendicular-polarization and using our processing.

Tables (2)

Tables Icon

Table 1 UIconM values for images of Fig. 10.

Tables Icon

Table 2 Comparison of algorithm runtime between conventional DCP method and our approach.

Equations (41)

Equations on this page are rendered with MathJax. Learn more.

I( x )= I A ( x )+ I F ( x )+ I A ( x )
I( x )= I A ( x )+ I B ( x )
I( x )=J( x )t( x )+A( 1t( x ) )
t( x )=exp( βd( x ) )
S=( I Q U V )
I= E 0x 2 + E 0y 2 Q= E 0x 2 E 0y 2 U=2 E 0x E 0y cosϕ V=2 E 0x E 0y sinϕ
S ' =MS( I Q U V )=( m 11 m 12 m 13 m 14 m 21 m 22 m 23 m 24 m 31 m 32 m 33 m 34 m 41 m 42 m 43 m 44 )( I Q U V )
M=( 1 M 12 ( θ ) 0 0 M 12 ( θ ) 1 0 0 0 0 M 33 ( θ ) 0 0 0 0 M 33 ( θ ) )
M 11 = M 22 =1 M 12 ( θ )= M 21 ( θ )= 1+ cos 2 ( θ ) 1+ cos 2 ( θ ) M 33 ( θ )= M 44 ( θ )= 2cos( θ ) 1+ cos 2 ( θ )
M=( 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 )
I( x,y )=S( x,y )+B( x,y )
I max ( x,y )= S max ( x,y )+ B max ( x,y )
I min ( x,y )= S min ( x,y )+ B min ( x,y )
P targ = S max ( x,y ) S min ( x,y ) S max ( x,y )+ S min ( x,y )
P scat = B max ( x,y ) B min ( x,y ) B max ( x,y )+ B min ( x,y )
S(x,y)= S max ( x,y )+ S min ( x,y )
B(x,y)= B max ( x,y )+ B min ( x,y )
S ˜ = 1 P scat P targ [ I min ( 1+ P scat ) I max ( 1 P scat ) ]
B ˜ = 1 P scat P targ [ I min ( 1 P scat ) I min ( 1+ P scat ) ]
S 5 = M pol2 M w2 M targ M w1 M pol1 S 0
M targ =( m 11 m 12 m 13 m 14 m 21 m 22 m 23 m 24 m 31 m 32 m 33 m 34 m 41 m 42 m 43 m 44 )
M w1 = M w2 =( 1 0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 )
M pol = 1 2 ( 1 cos( 2φ ) sin( 2φ ) 0 cos( 2φ ) cos 2 ( 2φ ) cos( 2φ )sin( 2φ ) 0 sin( 2φ ) cos( 2φ )sin( 2φ ) sin 2 ( 2φ ) 0 0 0 0 0 )
I \\ = 1 4 ( m t11 + m t12 + m t21 + m t22 m t11 + m t12 + m t21 + m t22 0 0 ) S 00
I = 1 4 ( m t11 + m t12 m t21 m t22 m t21 m t12 + m t11 + m t22 0 0 ) S 00
J dark (x)= min yΩ(x) ( min J c (y) cR,G,B )
I c (x) A c = J c (x) A c t(x)+1t( x )
min yΩ( x ) ( min cR,G,B I c ( y ) A c )={ min yΩ( x ) ( min cR,G,B J c ( y ) A c ) }t( x )+1t( x )
t ˜ (x)=1 min yΩ(x) ( min cR,G,B I c (y) A c )
J c (x)= I c (x) A c max( t ˜ (x),γ ) + A c
I B ( x )=A( 1t( x ) )
t ˜ (x)=1 I B ( x ) A
I f ( x )= G σ I( x )
I B ( x )= I f ( x ) σ f
J(x)= I(x)A max( t ˜ (x),γ) +A
UIconM=logAMEE( I )= 1 k 1 k 2 l=1 k 1 k=1 k 2 I max,k,l Θ I min,k,l I max,k,l I min,k,l ×log( I max,k,l Θ I min,k,l I max,k,l I min,k,l )
J c ( x )= I c ( x ) A c max( t ˜ c ( x ),γ ) + A c
t ˜ c (x)=1 I Bc ( x ) A c
t ˜ (x)=max[ t ˜ c ( x ) ]=1 min x [ I Bc ( x ) A c ]
I Bc ( x )= I fc ( x ) σ fc
I fc ( x )= G σ I( x )

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