Abstract
The underwater images suffer from low contrast and color distortion due to variable attenuation of light and nonuniform absorption of red, green and blue components. In this paper, we propose a Retinex-based underwater image enhancement approach. First, we perform underwater image enhancement using the contrast limited adaptive histogram equalization (CLAHE), which limits the noise and enhances the contrast of the dark components of the underwater image at the cost of blurring the visual information. Then, in order to restore the distorted colors, we perform the Retinex-based enhancement of the CLAHE processed image. Next, in order to restore the distorted edges and achieve smoothing of the blurred parts of image, we perform bilateral filtering on the Retinex processed image. In order to utilize the individual strengths of CLAHE, Retinex and bilateral filtering algorithms in a single framework, we determine the suitable parameter values. The qualitative and quantitative performance comparison with some of the existing approaches shows that the proposed approach achieves better enhancement of the underwater images.
Similar content being viewed by others
References
Ancuti C, Ancuti C, De Vleeschouwer C, Bekaert P (2018) Color balance and fusion for underwater image enhancement. IEEE Trans Image Process 27(1):379–393
Ancuti C, Ancuti C, Haber T, Bekaert P (2012) Enhancing underwater images, videos by fusion. In: Computer vision and pattern recognition. IEEE, pp 81–88
Bazeille S, Quidu I, Jaulin L, Malkasse J-P (2006) Automatic underwater image pre-processing. In: Proceedings of CMM’06
Bekaert P, Haber T, Ancuti C, Ancuti C (2012) Enhancing underwater images, videos by fusion. In: Computer vision and pattern recognition. IEEE, pp 81–88
Berman D, Treibitz T, Avidan S (2017) Diving into haze-lines; color restoration of underwater images. In: Proceedings of the British Machine Vision Conference (BMVC), vol 1
Carlevaris-Bianco N, Mohan A, Eustice RM (2010) Initial results in underwater single image dehazing. In: Oceans 2010 MTS/IEEE Seattle, pp 1–8
Chiang JY, Ying-Ching Chen A (2012) Underwater image enhancement by wavelength compensation and dehazing (wcid). IEEE Trans Image Process 21(4):1756–1769
Drews P, Nascimento E, Moraes F, Botelho S, Campos M (2013) Transmission estimation in underwater single images. In: IEEE international conference on computer vision workshops, pp 825–830
Emberton S, Chittka L, Cavallaro A (2015) Hierarchical rank-based veiling light estimation for underwater dehazing. In: Proceedings of the British Machine Vision Conference (BMVC), pp 125.1–125.12
Emberton S, Chittka L, Cavallaro A (2018) Underwater image and video dehazing with pure haze region segmentation. Comput Vis Image Underst 168:145–156
Fang S, Deng R, Cao Y, Fang C (2013) Effective single underwater image enhancement by fusion. J Comput 8(4):904–911
Farhadifard F, Zhou Z, von Lukas UF (2015) Learning-based underwater image enhancement with adaptive color mapping. In: International Symposium on Image and Signal Processing and Analysis (ISPA). IEEE, pp 48–53
Fu X, Zhuang P, Huang Y, Liao Y, Zhang X-P, Ding X (2014) A retinex-based enhancing approach for single underwater image. In: International Conference on Image Processing (ICIP). IEEE, pp 4572–4576
Galdran A, Pardo D, Picón A, Alvarez-Gila A (2015) Automatic red-channel underwater image restoration. J Vis Commun Image Represent 26:132–145
Garg D, Garg NK, Kumar M (2018) Underwater image enhancement using blending of CLAHE and percentile methodologies. Multimed Tools Appl 1–17
Hassan N, Ullah S, Bhatti N, Mahmood H, Zia M (2020) A cascaded approach for image defogging based on physical and enhancement models. Signal Image Video Process 1–9
Isa NAM, et al. (2012) Pixel distribution shifting color correction for digital color images. Appl Soft Comput 12(9):2948–2962
Jobson DJ, Rahman Z-U, Woodell GA (1997) A multiscale retinex for bridging the gap between color images and the human observation of scenes. IEEE Trans Image Process 6(7):965–976
Kim J-Y, Kim L-S, Hwang S-H (2001) An advanced contrast enhancement using partially overlapped sub-block histogram equalization. IEEE Trans Circ Syst Video Technol 11(4):475–484
Levedahl BA, Silverberg L (2009) Control of underwater vehicles in full unsteady flow. IEEE J Ocean Eng 34(4):656–668
Li C-Y, Guo J-C, Cong R-M, Pang Y-W, Wang B (2016) Underwater image enhancement by dehazing with minimum information loss and histogram distribution prior. IEEE Trans Image Process 25(12):5664–5677
Liu R, Fan X, Zhu M, Hou M, Luo Z Real-world underwater enhancement; Challenges, benchmarks, and solutions under natural light. IEEE Trans Circ Syst Video Technol
Lu H, Li Y, Serikawa S (2013) Underwater image enhancement using guided trigonometric bilateral filter and fast automatic color correction. In: International Conference on Image Processing (ICIP). IEEE, pp 3412–3416
Ludvigsen M, Sortland B, Johnsen G, Singh H (2007) Applications of geo-referenced underwater photo mosaics in marine biology and archaeology. Oceanography 20(4):140–149
Ng MK, Wang W (2011) A total variation model for retinex. SIAM J Img Sci 4(1):345–365
Panetta K, Gao C, Agaian S (2016) Human-visual-system-inspired underwater image quality measures. IEEE J Ocean Eng 41(3):541–551
Paris S, Kornprobst P, Tumblin J, Durand F, A gentle introduction to bilateral filtering and its applications (2007). In: SIGGRAPH ACM
Pizer SM, Johnston RE, Ericksen JP, Yankaskas BC, Muller KE (1990) Contrast-limited adaptive histogram equalization; Speed and effectiveness. In: Visualization in biomedical computing
Schechner YY, Averbuch Y Regularized image recovery in scattering media. IEEE Trans Pattern Anal Mach Intell 29(9)
Schettini R, Corchs S (2010) Underwater image processing; state of the art of restoration and image enhancement methods. EURASIP J Adv Signal Proc 2010 14
Serikawa S, Lu H (2014) Underwater image dehazing using joint trilateral filter. Comput Electr Eng 40(1):41–50
Wen H, Tian Y, Huang T, Gao W (2013) Single underwater image enhancement with a new optical model. In: International Symposium on Circuits and Systems (ISCAS). IEEE, pp 753–756
Yang H-Y, Chen P-Y, Huang C-C, Zhuang Y-Z, Shiau Y-H (2011) Low complexity underwater image enhancement based on dark channel prior. In: Innovations in Bio-inspired Computing and Applications (IBICA), pp 17–20
Zeyde R, Elad M, Protter M (2010) On single image scale-up using sparse-representations. In: International conference on curves and surfaces. Springer, pp 711–730
Zhang W, Li G, Ying Z (2017) A new underwater image enhancing method via color correction and illumination adjustment. In: Visual communications and image processing (VCIP). IEEE, pp 1–4
Zuiderveld K (1994) Contrast limited adaptive histogram equalization. In: Graphics gems IV. Academic Press Professional Inc., pp 474–485
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Hassan, N., Ullah, S., Bhatti, N. et al. The Retinex based improved underwater image enhancement. Multimed Tools Appl 80, 1839–1857 (2021). https://doi.org/10.1007/s11042-020-09752-2
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-020-09752-2