Generic placeholder image

International Journal of Sensors, Wireless Communications and Control

Author(s): Nishant Choudhary, Neha Goel* and Ravindra Kumar Yadav

DOI: 10.2174/0122103279259455231019092856

DownloadDownload PDF Flyer Cite As
A Study on Underwater Image Processing Techniques

Page: [353 - 360] Pages: 8

  • * (Excluding Mailing and Handling)

Abstract

In recent years, a potential interest has been developed in exploring and enhancing the quality of underwater images. The captured underwater images often experience scattering and high levels of noise due to the properties of light transit within the water and the biotic movement that occurs inside the ocean bottom. Underwater cameras or devices were fitted inside the unmanned underwater vehicles (UUVs), autonomous underwater vehicles (AUVs), remotely operated vehicles (ROVs), ocean detector networks, etc to see the ocean bottom. Despite being a crucial detector for keeping an eye on underwater landscapes, modern underwater camera sensors or detectors contain a number of problems. Numerous solutions to the issues with conventional underwater photography have been put out during the last five years. With the help of the number of contributions and difficulties reported by more than 40 researchers in their research article, this study focused to mention the current underwater image processing methods. This article represents an overview of numerous underwater image-processing techniques utilized, including underwater picture de-scattering, underwater image colour refurbishment, and underwater image aspect evaluations. Also, the latest trends, problems, and challenges for creating and processing underwater image sensors were discussed.

Graphical Abstract

[1]
McGlamery BL. A computer model for underwater camera system. Proc SPIE 1980; 208: 221-31.
[http://dx.doi.org/10.1117/12.958279]
[2]
Lu H, Li Y, Serikawa S. Computer vision for ocean observingArtificial Intelligence and Computer Vision. Cham: Springer 2016; pp. 1-16.
[3]
Bonin F, Burgeara A, Oliver G. Imaging system for advanced underwater vehicles. J Marit Res 2011; 8(1): 65-86.
[4]
Lu H, Li Y, Xu X, et al. Underwater image enhancement method using weighted guided trigonometric filtering and artificial light correction. J Vis Commun Image Represent 2016; 38: 504-16.
[http://dx.doi.org/10.1016/j.jvcir.2016.03.029]
[5]
Almurity O, Iqbal K, Hussain S, Mahmood A, Dhahri H. Underwater images contrast enhancement and its challenges: A survey. 2021. Available From: https://www.researcher-app.com/paper/7060439
[6]
Schechner Y, Averbuch Y. (2007) Regularized image recovery in scattering media. IEEE Transactions on Pattern Analysis and Machine Intelligence 29(9): 1655-60.
[7]
Tan C, Sluzek A, Jiang T. Range gated imaging system for underwater robotic vehicle. Proceedings of IEEE International Symposium on the Applications of Ferroelectrics. Singapore. IEEE 2007; pp. 1-7.
[8]
Kocak DM, Dalgleish FR, Caimi FM, Schechner YY. A focus on recent developments and trends in underwater imaging. Mar Technol Soc J 2008; 42(1): 52-67.
[http://dx.doi.org/10.4031/002533208786861209]
[9]
Tan C, Seet G, Sluzek A, He DM. A novel application of range-gated underwater laser imaging system (ULIS) in near-target turbid medium. Opt Lasers Eng 2005; 43(9): 995-1009.
[http://dx.doi.org/10.1016/j.optlaseng.2004.10.005]
[10]
Li H, Wang X, Bai T, Jin W, Huang Y, Ding K. Speckle noise suppression of range gated underwater imaging system. Appl Opt 2009; 38(18): 3937-44.
[11]
Arnold-Bos A, Malkasse J, Kerven G. A pre-processing framework for automatic underwater images denoising. Proceedings of the European Conference on Propagation and Systems. Breast, France. 2005; pp. 1-8.
[12]
Rizzi A, Gatta C, Marini D. A new algorithm for unsupervised global and local color correction. Pattern Recognit Lett 2003; 24(11): 1663-77.
[http://dx.doi.org/10.1016/S0167-8655(02)00323-9]
[13]
Arnold-Bos A, Malkasset J, Kervern G. Towards a model-free denoising of underwater optical images. Proceedings of the IEEE Europe Oceans Conference. Brest, France . IEEE 2005; pp. 527-32.
[http://dx.doi.org/10.1109/OCEANSE.2005.1511770]
[14]
Chambah M, Demani D, Renouf A, Courtellemont P, Rizzi A. Underwater color constancy: Enhancement of automatic live fish recognition. PROCEEDINGS OF SPIE, THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING 5293; 157-68.
[15]
Treibitz T, Schechner YY. Turbid scene enhancement using multi-directional illumination fusion. IEEE Trans Image Process 2012; 21(11): 4662-7.
[http://dx.doi.org/10.1109/TIP.2012.2208978] [PMID: 22829404]
[16]
Murez Z, Treibitz T, Ramamoorthi R, Kriegman D. Photometric stereo in a scattering medium. Proceedings of IEEE International Conference on Computer Vision. 3415-23.
[17]
Panetta K, Gao C, Agaian S. Human visual system inspired underwater image quality measures. IEEE J Oceanic Eng 2015; 1-11.
[18]
Roser M, Dunbabin M, Geiger A. Simultaneous underwater visibility assessment, enhancement and improved stereo. Proceedings of IEEE International Conference on Robotics and Automation. Hong Kong, China. IEEE 2014; pp. 1-8.
[http://dx.doi.org/10.1109/ICRA.2014.6907416]
[19]
Kaiming He, Jian Sun, Xiaoou Tang. Single image haze removal using dark channel prior. IEEE Trans Pattern Anal Mach Intell 2011; 33(12): 2341-53.
[http://dx.doi.org/10.1109/TPAMI.2010.168] [PMID: 20820075]
[20]
Chiang JY, Ying-Ching Chen. Underwater image enhancement by wavelength compensation and dehazing. IEEE Trans Image Process 2012; 21(4): 1756-69.
[http://dx.doi.org/10.1109/TIP.2011.2179666] [PMID: 22180510]
[21]
Yang M, Sowmya A. An underwater color image quality evaluation metric. IEEE Trans Image Process 2015; 24(12): 6062-71.
[http://dx.doi.org/10.1109/TIP.2015.2491020] [PMID: 26513783]
[22]
Lu H, Li Y, Serikawa S. Single underwater image descattering and color correction.Proc of IEEE International Conference on Acoustics, Speech and Signal Processing. South Brisbane, QLD, Australia. IEEE 2015; pp. 1623-7.
[http://dx.doi.org/10.1109/ICASSP.2015.7178245]
[23]
Ancuti C, Ancuti CO, Haber T, Bekaert P. Enhancing underwater images and videos by fusion. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. Providence, USA. 2012; p. 81-8.
[http://dx.doi.org/10.1109/CVPR.2012.6247661]
[24]
Galdran A, Pardo D, Picón A, Alvarez-Gila A. Automatic Red-Channel underwater image restoration. J Vis Commun Image Represent 2015; 26: 132-45.
[http://dx.doi.org/10.1016/j.jvcir.2014.11.006]
[25]
Gibson K. Preliminary results in using a joint contrast enhancement and turbulence mitigation method for underwater optical imaging. Proc of IEEE Oceans2015. Washington, DC, USA. IEEE. 2015; pp. 1-5.
[http://dx.doi.org/10.23919/OCEANS.2015.7404514]
[26]
Serikawa S, Lu H. Underwater image dehazing using joint trilateral filter. Comput Electr Eng 2014; 40(1): 41-50.
[http://dx.doi.org/10.1016/j.compeleceng.2013.10.016]
[27]
Bazeille S, Quidu I, Jaulin L, Malkasse JP. Automatic underwater image pre-processing CMM’06 - CARACTERISATION DU MILIEU MARIN.
[28]
Iqbal K, Salam R, Osman A, Talib A. Underwater image enhancement using an integrated color model. Int J Comput Sci 2007; 34(2): 1-8.
[29]
Torres-Mendez L, Dufdek G. Color correction of underwater images for aquatic robot inspection.Proc Of 5th International Workshop on Energy Minimization Method in Computer Vision and Pattern Recognition. Cham: Springer 2005; pp. 60-73.
[http://dx.doi.org/10.1007/11585978_5]
[30]
Åhlén J, Sundgren D, Bengtsson E. Application of underwater hyperspectral data for color correction purposes. Pattern Recognit Image Anal 2007; 17(1): 170-3.
[http://dx.doi.org/10.1134/S105466180701021X]
[31]
Petie F, Capelle-Laize A, Carre P. Underwater image enhancement by attenuation inversion with quaternions.Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing. Taipei, Taiwan. IEEE 2009; pp. 1177-80.
[http://dx.doi.org/10.1109/ICASSP.2009.4959799]
[32]
Lu H, Li Y, Zhang L, Serikawa S. Contrast enhancement for images in turbid water. J Opt Soc Am A Opt Image Sci Vis 2015; 32(5): 886-93.
[http://dx.doi.org/10.1364/JOSAA.32.000886] [PMID: 26366913]
[33]
Wang Z, Bovik AC, Sheikh HR, Simoncelli EP. Image quality assessment: From error visibility to structural similarity. IEEE Trans Image Process 2004; 13(4): 600-12.
[http://dx.doi.org/10.1109/TIP.2003.819861] [PMID: 15376593]
[34]
Lu H, Serikawa S. Underwater scene enhancement using weighted guided median filter.Proceedings of IEEE International Conference on Multimedia and Expo. Chengdu, China. IEEE 2014; pp. 1-6.
[http://dx.doi.org/10.1109/ICME.2014.6890157]
[35]
Hou W, Weidemann AD. Objectively assessing underwater image quality for the purpose of automated restoration. Proc SPIE 2007; 6575: 65750Q.
[http://dx.doi.org/10.1117/12.717789]
[36]
Arredondo M, Lebart K. A methodology for the systematic assessment of underwater video processing algorithms.Proceedings of IEEE Europe Oceans Conference. Brest, France. IEEE 2005; pp. 362-7.
[http://dx.doi.org/10.1109/OCEANSE.2005.1511741]
[37]
Lu H, Li Y, Xu X, He L, Dansereau D, Serikawa S. Underwater image descattering and quality assessment. Proceedings of IEEE International Conference on Image Processing. Phoenix, AZ, USA. IEEE 2016; pp. 1998-2002.
[38]
Fattal R. Single image dehazing. ACM Trans Graph 2008; 27(3): 1-9.
[http://dx.doi.org/10.1145/1360612.1360671]
[39]
Fattal R. Dehazing using color-lines. ACM Trans Graph 2014; 34(1): 1-14.
[http://dx.doi.org/10.1145/2651362]
[40]
Garcia R, Nicosevici T, Cufi C. On the way to solve lighting problems in underwater imaging OCEANS ’02 MTS/IEEE. Biloxi, MI, USA: IEEE 2002.
[http://dx.doi.org/10.1109/OCEANS.2002.1192107]
[41]
Zuiderveld K. Contrast limited adaptive histogram equalization Graphics Gems IV. Cambridge, Massachusetts: Academic Press 1994.
[42]
Schettini R, Corchs S. Underwater image processing: State of the art of restoration and image enhancement methods. EURASIP J Adv Signal Process 2010; 2010: 1-14.
[43]
Hou W. Ocean sensing and monitoring The International Society for Optics and Photonics
[44]
Li Y, Lu H, Li J, Li X, Li Y, Serikawa S. Underwater image de-scattering and classification by deep neural network. Comput Electr Eng 2016; 54: 68-77.
[http://dx.doi.org/10.1016/j.compeleceng.2016.08.008]
[45]
Zhang Y. GroRec: A group-centric intelligent recommender system integrating social, mobile and big data technologies. IEEE Trans Serv Comput 2016; 9(5): 786-95.
[http://dx.doi.org/10.1109/TSC.2016.2592520]
[46]
Zhang Y, Chen M, Huang D, Wu D, Li Y. iDoctor: Personalized and professionalized medical recommendations based on hybrid matrix factorization. Future Gener Comput Syst 2016; 47: 1-15.
[47]
Zhang Y, Chen M. Definable Networking. Cloud Based 5G. Wirel Netw 2016; 33-58.
[48]
Yemelyanov KM, Lin SS, Pugh EN Jr, Engheta N. Adaptive algorithms for two-channel polarization sensing under various polarization statistics with nonuniform distributions. Appl Opt 2006; 45(22): 5504-20.
[http://dx.doi.org/10.1364/AO.45.005504] [PMID: 16855649]
[49]
Schechner YY, Averbuch Y. Regularized image recovery in scattering media. IEEE Trans Pattern Anal Mach Intell 2007; 29(9): 1655-60.
[http://dx.doi.org/10.1109/TPAMI.2007.1141] [PMID: 17627052]