Enhancing underwater optical imaging by using a low-pass polarization filter

Khadidja Ould Amer; Marwa Elbouz; Ayman Alfalou; Christian Brosseau; Jaouad Hajjami

doi:10.1364/OE.27.000621

Enhancing underwater optical imaging by using a low-pass polarization filter

Khadidja Ould Amer, Marwa Elbouz, Ayman Alfalou, Christian Brosseau, and Jaouad Hajjami

Optics Express
Vol. 27,
Issue 2,
pp. 621-643
(2019)
•https://doi.org/10.1364/OE.27.000621

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Khadidja Ould Amer, Marwa Elbouz, Ayman Alfalou, Christian Brosseau, and Jaouad Hajjami, "Enhancing underwater optical imaging by using a low-pass polarization filter," Opt. Express 27, 621-643 (2019)

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Related Topics
Table of Contents Category
- Imaging Systems, Microscopy, and Displays
Optics & Photonics Topics
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The topics in this list come from the OSA Optics and Photonics Topics applied to this article.

About this Article
History
- Original Manuscript: October 3, 2018
- Revised Manuscript: November 14, 2018
- Manuscript Accepted: November 14, 2018
- Published: January 8, 2019

Accessible

Open Access

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.

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References

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Publication

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[Crossref] [PubMed]
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L. Mullen, B. Cochenour, W. Rabinovich, R. Mahon, and J. Muth, “Backscatter suppression for underwater modulating retroreflector links using polarization discrimination,” Appl. Opt. 48(2), 328–337 (2009).
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[Crossref]
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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]

2017 (3)

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]

S. Stocker, F. Foschum, P. Krauter, F. Bergmann, A. Hohmann, C. Scalfi Happ, and A. Kienle, “Broadband optical properties of milk,” Appl. Spectrosc. 71(5), 951–962 (2017).
[Crossref] [PubMed]

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).
[Crossref]

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]

J. D. van der Laan, D. A. Scrymgeour, S. A. Kemme, and E. L. Dereniak, “Detection range enhancement using circularly polarized light in scattering environments for infrared wavelengths,” Appl. Opt. 54(9), 2266–2274 (2015).
[Crossref] [PubMed]

2013 (3)

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]

I. Leonard, A. Alfalou, and C. Brosseau, “Sensitive test for sea mine identification based on polarization-aided image processing,” Opt. Express 21(24), 29283–29297 (2013).
[Crossref] [PubMed]

M. Dubreuil, P. Delrot, I. Leonard, A. Alfalou, C. Brosseau, and A. Dogariu, “Exploring underwater target detection by imaging polarimetry and correlation techniques,” Appl. Opt. 52(5), 997–1005 (2013).
[PubMed]

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)

T. Treibitz and Y. Y. Schechner, “Active polarization descattering,” IEEE Trans. Pattern Anal. Mach. Intell. 31(3), 385–399 (2009).
[Crossref] [PubMed]

L. Mullen, B. Cochenour, W. Rabinovich, R. Mahon, and J. Muth, “Backscatter suppression for underwater modulating retroreflector links using polarization discrimination,” Appl. Opt. 48(2), 328–337 (2009).
[Crossref] [PubMed]

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)

Y. Piederrière, F. Boulvert, J. Cariou, B. Le Jeune, Y. Guern, and G. Le Brun, “Backscattered speckle size as a function of polarization: influence of particle-size and- concentration,” Opt. Express 13(13), 5030–5039 (2005).
[Crossref] [PubMed]

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]

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).

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).
[Crossref] [PubMed]

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).
[Crossref] [PubMed]

1984 (1)

K. J. Voss and E. S. Fry, “Measurement of the Mueller matrix for ocean water,” Appl. Opt. 23(23), 4427–4439 (1984).
[Crossref] [PubMed]

1980 (1)

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]

1974 (1)

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

1967 (1)

G. D. Gilbert and J. C. Pernicka, “Improvement of underwater visibility by reduction of backscatter with a circular polarization technique,” Appl. Opt. 6(4), 741–746 (1967).
[Crossref] [PubMed]

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.

I. Leonard, A. Alfalou, and C. Brosseau, “Sensitive test for sea mine identification based on polarization-aided image processing,” Opt. Express 21(24), 29283–29297 (2013).
[Crossref] [PubMed]

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.

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.

S. Stocker, F. Foschum, P. Krauter, F. Bergmann, A. Hohmann, C. Scalfi Happ, and A. Kienle, “Broadband optical properties of milk,” Appl. Spectrosc. 71(5), 951–962 (2017).
[Crossref] [PubMed]

Bicout, D.

Boulvert, F.

Brennan, M. J.

A. Kouzoubov, M. J. Brennan, and J. C. Thomas, “Treatment of polarization in laser remote sensing of ocean water,” Appl. Opt. 37(18), 3873–3885 (1998).
[Crossref] [PubMed]

Brosseau, C.

I. Leonard, A. Alfalou, and C. Brosseau, “Sensitive test for sea mine identification based on polarization-aided image processing,” Opt. Express 21(24), 29283–29297 (2013).
[Crossref] [PubMed]

Caimi, F. M.

Cariou, J.

Chang, P. C.

J. G. Walker, P. C. Chang, and K. I. Hopcraft, “Visibility depth improvement in active polarization imaging in scattering media,” Appl. Opt. 39(27), 4933–4941 (2000).
[Crossref] [PubMed]

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.

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]

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.

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.

S. Stocker, F. Foschum, P. Krauter, F. Bergmann, A. Hohmann, C. Scalfi Happ, and A. Kienle, “Broadband optical properties of milk,” Appl. Spectrosc. 71(5), 951–962 (2017).
[Crossref] [PubMed]

Fry, E. S.

K. J. Voss and E. S. Fry, “Measurement of the Mueller matrix for ocean water,” Appl. Opt. 23(23), 4427–4439 (1984).
[Crossref] [PubMed]

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.

Giddings, T. E.

Gilbert, G. D.

G. D. Gilbert and J. C. Pernicka, “Improvement of underwater visibility by reduction of backscatter with a circular polarization technique,” Appl. Opt. 6(4), 741–746 (1967).
[Crossref] [PubMed]

Goldstein, D. L.

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]

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.

S. Stocker, F. Foschum, P. Krauter, F. Bergmann, A. Hohmann, C. Scalfi Happ, and A. Kienle, “Broadband optical properties of milk,” Appl. Spectrosc. 71(5), 951–962 (2017).
[Crossref] [PubMed]

Hopcraft, K. I.

J. G. Walker, P. C. Chang, and K. I. Hopcraft, “Visibility depth improvement in active polarization imaging in scattering media,” Appl. Opt. 39(27), 4933–4941 (2000).
[Crossref] [PubMed]

Isa, M.

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.

G. D. Lewis, D. L. Jordan, and P. J. Roberts, “Backscattering target detection in a turbid medium by polarization discrimination,” Appl. Opt. 38(18), 3937–3944 (1999).
[Crossref] [PubMed]

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.

G. W. Kattawar and M. J. Raković, “Virtues of mueller matrix imaging for underwater target detection,” Appl. Opt. 38(30), 6431–6438 (1999).
[Crossref] [PubMed]

Kemme, S. A.

Kienle, A.

S. Stocker, F. Foschum, P. Krauter, F. Bergmann, A. Hohmann, C. Scalfi Happ, and A. Kienle, “Broadband optical properties of milk,” Appl. Spectrosc. 71(5), 951–962 (2017).
[Crossref] [PubMed]

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.

A. Kouzoubov, M. J. Brennan, and J. C. Thomas, “Treatment of polarization in laser remote sensing of ocean water,” Appl. Opt. 37(18), 3873–3885 (1998).
[Crossref] [PubMed]

Krauter, P.

S. Stocker, F. Foschum, P. Krauter, F. Bergmann, A. Hohmann, C. Scalfi Happ, and A. Kienle, “Broadband optical properties of milk,” Appl. Spectrosc. 71(5), 951–962 (2017).
[Crossref] [PubMed]

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.

I. Leonard, A. Alfalou, and C. Brosseau, “Sensitive test for sea mine identification based on polarization-aided image processing,” Opt. Express 21(24), 29283–29297 (2013).
[Crossref] [PubMed]

Lewis, G. D.

G. D. Lewis, D. L. Jordan, and P. J. Roberts, “Backscattering target detection in a turbid medium by polarization discrimination,” Appl. Opt. 38(18), 3937–3944 (1999).
[Crossref] [PubMed]

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.

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.

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]

Nicosevici, T.

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).

Olmos-Antillon, A. T.

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

Ouyang, B.

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.

G. D. Gilbert and J. C. Pernicka, “Improvement of underwater visibility by reduction of backscatter with a circular polarization technique,” Appl. Opt. 6(4), 741–746 (1967).
[Crossref] [PubMed]

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]

Piederrière, Y.

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).
[Crossref] [PubMed]

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

Rabinovich, W.

Rakovic, M. J.

G. W. Kattawar and M. J. Raković, “Virtues of mueller matrix imaging for underwater target detection,” Appl. Opt. 38(30), 6431–6438 (1999).
[Crossref] [PubMed]

Roberts, P. J.

G. D. Lewis, D. L. Jordan, and P. J. Roberts, “Backscattering target detection in a turbid medium by polarization discrimination,” Appl. Opt. 38(18), 3937–3944 (1999).
[Crossref] [PubMed]

Sankpal, 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).

Scalfi Happ, C.

S. Stocker, F. Foschum, P. Krauter, F. Bergmann, A. Hohmann, C. Scalfi Happ, and A. Kienle, “Broadband optical properties of milk,” Appl. Spectrosc. 71(5), 951–962 (2017).
[Crossref] [PubMed]

Schechner, Y. Y.

T. Treibitz and Y. Y. Schechner, “Active polarization descattering,” IEEE Trans. Pattern Anal. Mach. Intell. 31(3), 385–399 (2009).
[Crossref] [PubMed]

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]

Schettini, R.

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).

Schmitt, J. M.

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).
[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]

Shahrizan, A.

Shaw, J. A.

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]

Shirron, J. J.

Sim, J. Y.

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]

Stocker, S.

S. Stocker, F. Foschum, P. Krauter, F. Bergmann, A. Hohmann, C. Scalfi Happ, and A. Kienle, “Broadband optical properties of milk,” Appl. Spectrosc. 71(5), 951–962 (2017).
[Crossref] [PubMed]

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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).
[Crossref] [PubMed]

Tang, X.

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]

Thomas, J. C.

A. Kouzoubov, M. J. Brennan, and J. C. Thomas, “Treatment of polarization in laser remote sensing of ocean water,” Appl. Opt. 37(18), 3873–3885 (1998).
[Crossref] [PubMed]

Treibitz, T.

T. Treibitz and Y. Y. Schechner, “Active polarization descattering,” IEEE Trans. Pattern Anal. Mach. Intell. 31(3), 385–399 (2009).
[Crossref] [PubMed]

Trucco, E.

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

Tyo, J. S.

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]

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J. G. Walker, P. C. Chang, and K. I. Hopcraft, “Visibility depth improvement in active polarization imaging in scattering media,” Appl. Opt. 39(27), 4933–4941 (2000).
[Crossref] [PubMed]

Weitz, D. A.

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]

Won, C. 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]

Yun, 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]

Zerr, B.

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).

Zhang, 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]

Zhu, J. X.

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]

Advances in Computational Sciences and Technology (1)

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).

Appl. Opt. (10)

A. Kouzoubov, M. J. Brennan, and J. C. Thomas, “Treatment of polarization in laser remote sensing of ocean water,” Appl. Opt. 37(18), 3873–3885 (1998).
[Crossref] [PubMed]

K. J. Voss and E. S. Fry, “Measurement of the Mueller matrix for ocean water,” Appl. Opt. 23(23), 4427–4439 (1984).
[Crossref] [PubMed]

G. D. Lewis, D. L. Jordan, and P. J. Roberts, “Backscattering target detection in a turbid medium by polarization discrimination,” Appl. Opt. 38(18), 3937–3944 (1999).
[Crossref] [PubMed]

G. D. Gilbert and J. C. Pernicka, “Improvement of underwater visibility by reduction of backscatter with a circular polarization technique,” Appl. Opt. 6(4), 741–746 (1967).
[Crossref] [PubMed]

J. G. Walker, P. C. Chang, and K. I. Hopcraft, “Visibility depth improvement in active polarization imaging in scattering media,” Appl. Opt. 39(27), 4933–4941 (2000).
[Crossref] [PubMed]

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]

G. W. Kattawar and M. J. Raković, “Virtues of mueller matrix imaging for underwater target detection,” Appl. Opt. 38(30), 6431–6438 (1999).
[Crossref] [PubMed]

Appl. Soft Comput. J (1)

Appl. Spectrosc. (1)

S. Stocker, F. Foschum, P. Krauter, F. Bergmann, A. Hohmann, C. Scalfi Happ, and A. Kienle, “Broadband optical properties of milk,” Appl. Spectrosc. 71(5), 951–962 (2017).
[Crossref] [PubMed]

Cmm (1)

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

EURASIP J. Adv. Signal Process. (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).

EURASIP J. Image Video Process. (1)

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]

IEEE J. Oceanic Eng. (4)

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

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]

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

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]

In Oceans'02 MTS/IEEE (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).

International Society for Optics and Photonics (1)

International Society for Optics and Photonics, In Ocean Optics VI. (1)

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]

J. Vis. Commun. Image Represent. (2)

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]

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]

Mob. Netw. Appl. (2)

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]

Opt. Asp. Oceanogr (1)

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

Opt. Express (2)

I. Leonard, A. Alfalou, and C. Brosseau, “Sensitive test for sea mine identification based on polarization-aided image processing,” Opt. Express 21(24), 29283–29297 (2013).
[Crossref] [PubMed]

Phys. Rev. B Condens. Matter (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).
[Crossref] [PubMed]

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

Trait. du Signal (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).

Other (6)

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).

M. S. Hitam, “ Mixture contrast limited adaptive histogram equalization for underwater image enhancement,” Computer Applications Technology (ICCAT), 1–5 (2013).

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]

L. Bartolini, L. De Dominicis, M. Ferri De Collibus, G. Fornetti, M. Francucci, M. Guarneri, E. Paglia, C. Poggi, and R. Ricci, “ Polarimetry as tool to improve phase measurement in an amplitude modulated laser for submarine archaeological sites inspection,” Proc. SPIE - Int. Soc. Opt. Eng 1 (7), 1–12 (2007).

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. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Fig. 1 Absorption and scattering in water.

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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.

Download Full Size | PPT Slide | PDF

Fig. 3 (a) Light source and camera with polarizers. (b) The used experimental set-up based on polarization.

Download Full Size | PPT Slide | PDF

Fig. 4 Images of the target for two different turbidity conditions (top row:

μ_{s} = 0.056 c m^{- 1}, τ_{0} = 1.96

), (bottom row

μ_{s} = 0.084 c m^{- 1}, τ_{0} = 2.94

). (a) and (d): unpolarized images; (b) and (e) parallel polarization images; (c) and (f). Cross-perpendicular polarization images.

Download Full Size | PPT Slide | PDF

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.

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Fig. 6 Image of marker for different turbidity conditions (from left to right: (a) clear water, (b) turbidity

μ_{s 1}

,(c) turbidity

μ_{s 2}

,(d) turbidity

μ_{s 3}

.Top row: unpolarized images, bottom row: the corresponding cross linear polarization images.

Download Full Size | PPT Slide | PDF

Fig. 7 Image of marker (capital letter P) at turbidity

μ_{s 2}

. (a) Without polarization. (b) With cross linear polarization.

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Fig. 8 Principle of our algorithm for grayscale images.

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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} = 0.056 c m^{- 1}, τ_{0} = 1.96

, when skim milk is added, and (c) as in (b) with turbidity

μ_{s} = 0.084 c m^{- 1}, τ_{0} = 2.94

Download Full Size | PPT Slide | PDF

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).

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Fig. 11 (a) Input image. A comparison of transmission map between: (b) DCP and (c) our method.

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Fig. 12 Principle of our algorithm for color images.

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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).

Download Full Size | PPT Slide | PDF

Fig. 14 The top row of each block of images corresponds to turbidity condition (

μ_{s} = 0.056 c 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.

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Fig. 15 Underwater imaging system.

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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.

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Tables (2)

Table 1 UIconM values for images of Fig. 10.

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

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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 (1 - t (x))

t (x) = \exp (- β \cdot d (x))

S = (\begin{matrix} I \\ Q \\ U \\ V \end{matrix})

\begin{matrix} I = E_{0 x}^{2} + E_{0 y}^{2} \\ Q = E_{0 x}^{2} - E_{0 y}^{2} \\ U = 2 E_{0 x} E_{0 y} \cos ϕ \\ V = 2 E_{0 x} E_{0 y} \sin ϕ \end{matrix}

S^{'} = M \cdot S \Leftrightarrow (\begin{matrix} I^{'} \\ Q^{'} \\ U^{'} \\ V^{'} \end{matrix}) = (\begin{matrix} 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} \end{matrix}) \cdot (\begin{matrix} I \\ Q \\ U \\ V \end{matrix})

M = (\begin{matrix} 1 & M_{12} (θ) & 0 & 0 \\ M_{12} (θ) & 1 & 0 & 0 \\ 0 & 0 & M_{33} (θ) & 0 \\ 0 & 0 & 0 & M_{33} (θ) \end{matrix})

\begin{matrix} M_{11} = M_{22} = 1 \\ M_{12} (θ) = M_{21} (θ) = \frac{- 1 + \cos^{2} (θ)}{1 + \cos^{2} (θ)} \\ M_{33} (θ) = M_{44} (θ) = \frac{2 \cdot \cos (θ)}{1 + \cos^{2} (θ)} \end{matrix}

M = (\begin{matrix} 1 & 0 & 0 & 0 \\ 0 & 1 & 0 & 0 \\ 0 & 0 & - 1 & 0 \\ 0 & 0 & 0 & - 1 \end{matrix})

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_{t \arg} = \frac{S_{\max} (x, y) - S_{\min} (x, y)}{S_{\max} (x, y) + S_{\min} (x, y)}

P_{s c a t} = \frac{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)

\tilde{S} = \frac{1}{P_{s c a t} - P_{t \arg}} [I_{\min} (1 + P_{s c a t}) - I_{\max} (1 - P_{s c a t})]

\tilde{B} = \frac{1}{P_{s c a t} - P_{t \arg}} [I_{\min} (1 - P_{s c a t}) - I_{\min} (1 + P_{s c a t})]

S_{5} = M_{p o l 2} M_{w 2} M_{t \arg} M_{w 1} M_{p o l 1} S_{0}

M_{t \arg} = (\begin{matrix} 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} \end{matrix})

M_{w 1} = M_{w 2} = (\begin{matrix} 1 & 0 & 0 & 0 \\ 0 & 1 & 0 & 0 \\ 0 & 0 & - 1 & 0 \\ 0 & 0 & 0 & - 1 \end{matrix})

M_{p o l} = \frac{1}{2} (\begin{matrix} 1 & \cos (2 φ) & \sin (2 φ) & 0 \\ \cos (2 φ) & \cos^{2} (2 φ) & \cos (2 φ) \sin (2 φ) & 0 \\ \sin (2 φ) & \cos (2 φ) \sin (2 φ) & \sin^{2} (2 φ) & 0 \\ 0 & 0 & 0 & 0 \end{matrix})

I_{\ \} = \frac{1}{4} (\begin{matrix} m_{t 11} + m_{t 12} + m_{t 21} + m_{t 22} \\ m_{t 11} + m_{t 12} + m_{t 21} + m_{t 22} \\ 0 \\ 0 \end{matrix}) \cdot S_{00}

I_{⊥} = \frac{1}{4} (\begin{matrix} m_{t 11} + m_{t 12} - m_{t 21} - m_{t 22} \\ m_{t 21} - m_{t 12} + m_{t 11} + m_{t 22} \\ 0 \\ 0 \end{matrix}) \cdot S_{00}

J^{d a r k} (x) = \min_{y \in Ω (x)} (\underset{c \in R, G, B}{\min J^{c} (y)})

\frac{I^{c} (x)}{A^{c}} = \frac{J^{c} (x)}{A^{c}} \cdot t (x) + 1 - t (x)

\min_{y \in Ω (x)} (\min_{c \in R, G, B} \frac{I^{c} (y)}{A^{c}}) = {\min_{y \in Ω (x)} (\min_{c \in R, G, B} \frac{J^{c} (y)}{A^{c}})} t (x) + 1 - t (x)

\tilde{t} (x) = 1 - \min_{y \in Ω (x)} (\min_{c \in R, G, B} \frac{I^{c} (y)}{A^{c}})

J_{c} (x) = \frac{I_{c} (x) - A_{c}}{\max (\tilde{t} (x), γ)} + A_{c}

I_{B} (x) = A (1 - t (x))

\tilde{t} (x) = 1 - \frac{I_{B} (x)}{A}

I_{f} (x) = G_{σ} \cdot I (x)

I_{B} (x) = I_{f} (x) - σ_{f}

J (x) = \frac{I (x) - A}{\max (\tilde{t} (x), γ)} + A

\begin{matrix} UIconM = logAMEE (I) = \\ \frac{1}{k_{1} k_{2}} \otimes \sum_{l = 1}^{k_{1}} \sum_{k = 1}^{k_{2}} \frac{I_{\max, k, l} Θ I_{\min, k, l}}{I_{\max, k, l} \oplus I_{\min, k, l}} \times \log (\frac{I_{\max, k, l} Θ I_{\min, k, l}}{I_{\max, k, l} \oplus I_{\min, k, l}}) \end{matrix}

J_{c} (x) = \frac{I_{c} (x) - A_{c}}{\max ({\tilde{t}}_{c} (x), γ)} + A_{c}

{\tilde{t}}_{c} (x) = 1 - \frac{I_{B c} (x)}{A_{c}}

\tilde{t} (x) = \max [{\tilde{t}}_{c} (x)] = 1 - \min_{x} [\frac{I_{B c} (x)}{A_{c}}]

I_{B c} (x) = I_{f c} (x) - σ_{f c}

I_{f c} (x) = G_{σ} I (x)

	Figure 10(a)	Figure 10(b)	Figure 10(c)	Figure 10(d)
UIconM	0.1431	0.2418	0.1637	0.2552
	Figure 10(e)	Figure 10(f)	Figure 10(g)	Figure 10(h)
UIconM	0.1044	0.2175	0.2021	0.2385

Image (i)	1	2	3	4	5
Image size	[644 $\times$ 858]	[1287 $\times$ 1716]	[1930 $\times$ 2573]	[2573 $\times$ 3431]	[3216 $\times$ 4288]
Runtime (s)DCP	6.64	27.36	62.72	111.73	176.37
Runtime (s)our method	0.17	0.53	1.45	2.68	3.57

	Figure 10(a)	Figure 10(b)	Figure 10(c)	Figure 10(d)
UIconM	0.1431	0.2418	0.1637	0.2552
	Figure 10(e)	Figure 10(f)	Figure 10(g)	Figure 10(h)
UIconM	0.1044	0.2175	0.2021	0.2385

Image (i)	1	2	3	4	5
Image size	[644 $\times$ 858]	[1287 $\times$ 1716]	[1930 $\times$ 2573]	[2573 $\times$ 3431]	[3216 $\times$ 4288]
Runtime (s)DCP	6.64	27.36	62.72	111.73	176.37
Runtime (s)our method	0.17	0.53	1.45	2.68	3.57

Abstract

References

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