Multi-Purpose Oriented Real-World Underwater Image Enhancement

Images captured underwater usually suffer from weak illumination, color cast, fuzz and noise, which severely degrade the visibility. Numerous methods have been proposed to improve the quality of underwater images, but rarely of them can give a comprehensive consideration to all these problems, which makes them hard to adapt for various and complex real-world underwater scenes. Herein, a novel multi-purpose oriented approach for real-world underwater image enhancement is proposed. To manipulate different information on the corresponding layers, we firstly decompose the input image into illumination layer and reflectance layer. Subsequently, compensation of the brightness is carried out on the illumination layer, while color correction and contrast enhancement are implemented on the reflectance layer through a multi-scale processing strategy. Benefiting from this strategy, the proposed approach is provided with high control flexibility, which can significantly improve the visibility of underwater images while efficiently suppress the amplification of noise. Both qualitative and quantitative evaluations demonstrate that the proposed method has superior robustness, accuracy and effectiveness for complex marine circumstance.

[1]  Anne E. James,et al.  Enhancing the low quality images using Unsupervised Colour Correction Method , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.

[2]  Hanyu Li,et al.  Underwater Image Enhancement Using a Multiscale Dense Generative Adversarial Network , 2020, IEEE Journal of Oceanic Engineering.

[3]  Adrian Galdran,et al.  Automatic Red-Channel underwater image restoration , 2015, J. Vis. Commun. Image Represent..

[4]  Mateu Sbert,et al.  Color Channel Compensation (3C): A Fundamental Pre-Processing Step for Image Enhancement , 2019, IEEE Transactions on Image Processing.

[5]  Xinghao Ding,et al.  Two-step approach for single underwater image enhancement , 2017, 2017 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS).

[6]  Xiao-Ping Zhang,et al.  A retinex-based enhancing approach for single underwater image , 2014, 2014 IEEE International Conference on Image Processing (ICIP).

[7]  Wei Song,et al.  An Experimental-Based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging , 2019, IEEE Access.

[8]  Wen Gao,et al.  Single underwater image enhancement with a new optical model , 2013, 2013 IEEE International Symposium on Circuits and Systems (ISCAS2013).

[9]  Zhipeng Feng,et al.  Underwater Image Enhancement Using Scene Depth-Based Adaptive Background Light Estimation and Dark Channel Prior Algorithms , 2019, IEEE Access.

[10]  Srimanta Mandal,et al.  Local Proximity for Enhanced Visibility in Haze , 2019, IEEE Transactions on Image Processing.

[11]  Jie Li,et al.  WaterGAN: Unsupervised Generative Network to Enable Real-Time Color Correction of Monocular Underwater Images , 2017, IEEE Robotics and Automation Letters.

[12]  N Carlevaris-Bianco,et al.  Initial results in underwater single image dehazing , 2010, OCEANS 2010 MTS/IEEE SEATTLE.

[13]  A. Sluzek,et al.  A novel application of range-gated underwater laser imaging system (ULIS) in near-target turbid medium , 2005 .

[14]  Xiao-Ping Zhang,et al.  A Weighted Variational Model for Simultaneous Reflectance and Illumination Estimation , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[15]  Dacheng Tao,et al.  An Underwater Image Enhancement Benchmark Dataset and Beyond , 2019, IEEE Transactions on Image Processing.

[16]  Chenggang Dai,et al.  Dual-Purpose Method for Underwater and Low-Light Image Enhancement via Image Layer Separation , 2019, IEEE Access.

[17]  Arcot Sowmya,et al.  An Underwater Color Image Quality Evaluation Metric , 2015, IEEE Transactions on Image Processing.

[18]  Jean-Philippe Tarel,et al.  Fast visibility restoration from a single color or gray level image , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[19]  Chen Gao,et al.  Human-Visual-System-Inspired Underwater Image Quality Measures , 2016, IEEE Journal of Oceanic Engineering.

[20]  Md Jahidul Islam,et al.  Enhancing Underwater Imagery Using Generative Adversarial Networks , 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).

[21]  Herng-Hua Chang,et al.  Single Underwater Image Restoration Based on Adaptive Transmission Fusion , 2020, IEEE Access.

[22]  Mario Fernando Montenegro Campos,et al.  Underwater Depth Estimation and Image Restoration Based on Single Images , 2016, IEEE Computer Graphics and Applications.

[23]  Yoav Y. Schechner,et al.  Regularized Image Recovery in Scattering Media , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[24]  Mohinder Malhotra Single Image Haze Removal Using Dark Channel Prior , 2016 .

[25]  Yang Yan,et al.  Jointly adversarial networks for wavelength compensation and dehazing of underwater images , 2019, Multimedia Tools and Applications.

[26]  Silvia Silva da Costa Botelho,et al.  Transmission Estimation in Underwater Single Images , 2013, 2013 IEEE International Conference on Computer Vision Workshops.

[27]  Chunle Guo,et al.  Emerging From Water: Underwater Image Color Correction Based on Weakly Supervised Color Transfer , 2017, IEEE Signal Processing Letters.

[28]  Zeev Farbman,et al.  Edge-preserving decompositions for multi-scale tone and detail manipulation , 2008, ACM Trans. Graph..

[29]  B. L. McGlamery,et al.  A Computer Model For Underwater Camera Systems , 1980, Other Conferences.

[30]  Seiichi Serikawa,et al.  Low-Light Underwater Image Enhancement for Deep-Sea Tripod , 2019, IEEE Access.

[31]  Zhou Wang,et al.  A Patch-Structure Representation Method for Quality Assessment of Contrast Changed Images , 2015, IEEE Signal Processing Letters.

[32]  Tom Goldstein,et al.  The Split Bregman Method for L1-Regularized Problems , 2009, SIAM J. Imaging Sci..

[33]  Pamela C. Cosman,et al.  Underwater Image Restoration Based on Image Blurriness and Light Absorption , 2017, IEEE Transactions on Image Processing.

[34]  Pamela C. Cosman,et al.  Generalization of the Dark Channel Prior for Single Image Restoration , 2018, IEEE Transactions on Image Processing.

[35]  Fatih Murat Porikli,et al.  Underwater scene prior inspired deep underwater image and video enhancement , 2020, Pattern Recognit..

[36]  Ying-Ching Chen,et al.  Underwater Image Enhancement by Wavelength Compensation and Dehazing , 2012, IEEE Transactions on Image Processing.

[37]  Andrea Cavallaro,et al.  Hierarchical rank-based veiling light estimation for underwater dehazing , 2015, BMVC.

[38]  Codruta O. Ancuti,et al.  Enhancing underwater images and videos by fusion , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[39]  Ting Wang,et al.  Underwater image enhancement via extended multi-scale Retinex , 2017, Neurocomputing.