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Review Article |

A Review of Methods of Removing Haze from An Image

Author(s): Kholud A. Karoon1 and Zainab. N. Nemer2

Published In : International Journal of Electrical and Electronics Research (IJEER)        Volume 10, Issue 3

Publisher : FOREX Publication

Published : 30 September 2022

e-ISSN : 2347-470X

Page(s) : 742-746

DOI: https://doi.org/10.37391/IJEER.100354

Abstract

A literature review aids in comprehending and gaining further information about a certain area of a subject. The presence of haze, fog, smoke, rain, and other harsh weather conditions affects outdoor photos. Images taken in unnatural weather have weak contrast and poor colors. This may make detecting objects in the produced hazy pictures difficult. In computer vision, scenes and images taken in a foggy atmosphere suffer from blurring. This work covers a study of many remove haze algorithms for eliminating haze collected in real-world weather scenarios in order to recover haze-free images rapidly and with improved quality. The contrast, viewing range, and color accuracy have been enhanced. All of these techniques it is used in countless fields. Some of the applications that use this technology outdoor surveillance, object recognition, underwater photography, and so on.

Keywords: Methods of de-hazing, outdoor images, De-hazing, AOD-Net




Kholud A. Karoon*, Department of Computer Science, College of Computer Science and Information Technology, University of Basrah, Basrah, Iraq; Email: itpg.kholud.karoon@uobasrah.edu.iq

Zainab. N. Nemer, Department of Computer Science, College of Computer Science and Information Technology, University of Basrah, Basrah, Iraq

    [1] M. Alabbas, R. S. Khudeyer, and S. Jaf, "Improved Arabic characters recognition by combining multiple machine learning classifiers," in 2016 International Conference on Asian Language Processing (IALP), 2016, pp. 262-265: IEEE.[Cross Ref]
    [2] N. M. A.-M. M. Al and R. S. J. I. Khudeyer, "ResNet-34/DR: A Residual Convolutional Neural Network for the Diagnosis of Diabetic Retinopathy," vol. 45, no. 7, 2021.[Cross Ref]
    [3] Ajeeta Singh Bhadoria, Vandana Vikas Thakre (2020), Improved Single Haze Removal using Weighted Filter and Gaussian-Laplacian Method. IJEER 8(2), 26-31. DOI: 10.37391/IJEER.080201. [Cross Ref]
    [4] B. Das, J. P. Ebenezer, and S. J. T. V. C. Mukhopadhyay, "A comparative study of single image fog removal methods," pp. 1-17, 2020.[Cross Ref]
    [5] D. Singh, V. Kumar, and M. J. A. I. Kaur, "Single image dehazing using gradient channel prior," vol. 49, no. 12, pp. 4276-4293, 2019.[Cross Ref]
    [6] F. Wang, S. Yao, H. Luo, and B. J. R. S. Huang, "Estimating High-Resolution PM2. 5 Concentrations by Fusing Satellite AOD and Smartphone Photographs Using a Convolutional Neural Network and Ensemble Learning," vol. 14, no. 6, p. 1515, 2022.[Cross Ref]
    [7] Hee-Chul Kim (2022), A Study on Edge Board for Blur Image Judgment and Cluster Image Behavior Analysis: AI-Based Image Processing System Research. IJEER 10(2), 218-224. DOI: 10.37391/IJEER.100229.[Cross Ref]
    [8] B. Li et al., "Reside: A benchmark for single image dehazing," vol. 1, 2017.[Cross Ref]
    [9] G. Yang and A. N. J. J. o. R.-T. I. P. Evans, "Improved single image dehazing methods for resource-constrained platforms," vol. 18, no. 6, pp. 2511-2525, 2021.[Cross Ref]
    [10] S. Yelmanov and Y. Romanyshyn, "Image enhancement in automatic mode by piecewise nonlinear contrast stretching," in 2018 IEEE First International Conference on System Analysis & Intelligent Computing (SAIC), 2018, pp. 1-6: IEEE.[Cross Ref]
    [11] W. Wang, Z. Chen, X. Yuan, and X. J. I. S. Wu, "Adaptive image enhancement method for correcting low-illumination images," vol. 496, pp. 25-41, 2019.[Cross Ref]
    [12] Y. Chang, C. Jung, P. Ke, H. Song, and J. J. I. A. Hwang, "Automatic contrast-limited adaptive histogram equalization with dual gamma correction," vol. 6, pp. 11782-11792, 2018.[Cross Ref]
    [13] S.Abinaya and T.Rajasenbagam (2022), Enhanced Visual Analytics Technique for Content-Based Medical Image Retrieval. IJEER 10(2), 93-99. DOI: 10.37391/IJEER.100207. [Cross Ref]
    [14] J. Zhou, J. Yao, W. Zhang, D. J. M. T. Zhang, and Applications, "Multi-scale retinex-based adaptive gray-scale transformation method for underwater image enhancement," vol. 81, no. 2, pp. 1811-1831, 2022.[Cross Ref]
    [15] M. Veluchamy and B. J. O. Subramani, "Image contrast and color enhancement using adaptive gamma correction and histogram equalization," vol. 183, pp. 329-337, 2019.[Cross Ref]
    [16] V. S. Prasath, D. N. Thanh, and N. H. Hai, "On selecting the appropriate scale in image selective smoothing by nonlinear diffusion," in 2018 IEEE Seventh International Conference on Communications and Electronics (ICCE), 2018, pp. 267-272: IEEE.[Cross Ref]
    [17] M. Ju, C. Ding, D. Zhang, Y. J. J. I. T. o. C. Guo, and S. f. V. Technology, "BDPK: Bayesian dehazing using prior knowledge," vol. 29, no. 8, pp. 2349-2362, 2018.[Cross Ref]
    [18] J. Kopf et al., "Deep photo: Model-based photograph enhancement and viewing," vol. 27, no. 5, pp. 1-10, 2008.[Cross Ref]
    [19] C. O. Ancuti and C. J. I. T. o. I. P. Ancuti, "Single image dehazing by multi-scale fusion," vol. 22, no. 8, pp. 3271-3282, 2013.[Cross Ref]
    [20] L. K. Choi, J. You, and A. C. J. I. T. o. I. P. Bovik, "Referenceless prediction of perceptual fog density and perceptual image defogging," vol. 24, no. 11, pp. 3888-3901, 2015.[Cross Ref]
    [21] A. Galdran, J. Vazquez-Corral, D. Pardo, and M. J. S. J. o. I. S. Bertalmio, "Enhanced variational image dehazing," vol. 8, no. 3, pp. 1519-1546, 2015.[Cross Ref]
    [22] Z. Yu, B. Sun, D. Liu, V. W. De Dravo, M. Khokhlova, and S. J. J. o. R. M. Wu, "STRASS Dehazing: Spatio-Temporal Retinex-Inspired Dehazing by an Averaging of Stochastic Samples," vol. 10, no. 5, p. 1381, 2022.[Cross Ref]
    [23] A. Galdran, J. Vazquez-Corral, D. Pardo, and M. J. I. S. P. L. Bertalmio, "Fusion-based variational image dehazing," vol. 24, no. 2, pp. 151-155, 2016.[Cross Ref]
    [24] B.-H. Chen and S.-C. J. J. o. D. T. Huang, "Edge collapse-based dehazing algorithm for visibility restoration in real scenes," vol. 12, no. 9, pp. 964-970, 2016.[Cross Ref]
    [25] B.-H. Chen, S.-C. J. A. T. o. M. C. Huang, Communications, and Applications, "An advanced visibility restoration algorithm for single hazy images," vol. 11, no. 4, pp. 1-21, 2015.[Cross Ref]
    [26] K. He, J. Sun, X. J. I. t. o. p. a. Tang, and m. intelligence, "Single image haze removal using dark channel prior," vol. 33, no. 12, pp. 2341-2353, 2010.[Cross Ref]
    [27] R. T. Tan, "Visibility in bad weather from a single image," in 2008 IEEE conference on computer vision and pattern recognition, 2008, pp. 1-8: IEEE.[Cross Ref]
    [28] R. J. A. t. o. g. Fattal, "Single image dehazing," vol. 27, no. 3, pp. 1-9, 2008.[Cross Ref]
    [29] R. J. A. t. o. g. Fattal, "Dehazing using color-lines," vol. 34, no. 1, pp. 1-14, 2014.[Cross Ref]
    [30] A. Levin, D. Lischinski, Y. J. I. t. o. p. a. Weiss, and m. intelligence, "A closed-form solution to natural image matting," vol. 30, no. 2, pp. 228-242, 2007.[Cross Ref]
    [31] D. K. Jha, B. Gupta, and S. S. J. I. C. V. Lamba, "l2‐norm‐based prior for haze‐removal from single image," vol. 10, no. 5, pp. 331-343, 2016.[Cross Ref]
    [32] S.-C. Huang, J.-H. Ye, and B.-H. J. I. T. o. I. E. Chen, "An advanced single-image visibility restoration algorithm for real-world hazy scenes," vol. 62, no. 5, pp. 2962-2972, 2014.[Cross Ref]
    [33] L. Zeng and Y. J. C. J. o. E. Dai, "Single image dehazing based on combining dark channel prior and scene radiance constraint," vol. 25, no. 6, pp. 1114-1120, 2016.[Cross Ref]
    [34] S.-C. Huang, B.-H. Chen, and Y.-J. J. I. T. o. I. T. S. Cheng, "An efficient visibility enhancement algorithm for road scenes captured by intelligent transportation systems," vol. 15, no. 5, pp. 2321-2332, 2014.[Cross Ref]
    [35] K. B. Gibson, D. T. Vo, and T. Q. J. I. t. o. i. p. Nguyen, "An investigation of dehazing effects on image and video coding," vol. 21, no. 2, pp. 662-673, 2011.[Cross Ref]
    [36] T. Naseeba and H. J. I. R. J. E. T. Binu, "KP Visibility Restoration of Single Hazy Images Captured in Real-World Weather Conditions," vol. 3, pp. 135-139, 2016.[Cross Ref]
    [37] J. Yu, C. Xiao, and D. Li, "Physics-based fast single image fog removal," in IEEE 10th International Conference on Signal Processing Proceedings, 2010, pp. 1048-1052: IEEE.[Cross Ref]
    [38] C. Xiao and J. J. T. V. C. Gan, "Fast image dehazing using guided joint bilateral filter," vol. 28, no. 6, pp. 713-721, 2012.[Cross Ref]
    [39] G. Meng, Y. Wang, J. Duan, S. Xiang, and C. Pan, "Efficient image dehazing with boundary constraint and contextual regularization," in Proceedings of the IEEE international conference on computer vision, 2013, pp. 617-624.[Cross Ref]
    [40] J. K. Kim, P. Knag, T. Chen, and Z. Zhang, "A 640M pixel/s 3.65 mW sparse event-driven neuromorphic object recognition processor with on-chip learning," in 2015 Symposium on VLSI Circuits (VLSI Circuits), 2015, pp. C50-C51: IEEE.[Cross Ref]
    [41] L. He, J. Zhao, N. Zheng, and D. J. I. T. o. I. P. Bi, "Haze removal using the difference-structure-preservation prior," vol. 26, no. 3, pp. 1063-1075, 2016.[Cross Ref]
    [42] Y.-H. Lai, Y.-L. Chen, C.-J. Chiou, C.-T. J. I. T. o. C. Hsu, and S. f. V. Technology, "Single-image dehazing via optimal transmission map under scene priors," vol. 25, no. 1, pp. 1-14, 2014.[Cross Ref]
    [43] J.-H. Kim, W.-D. Jang, J.-Y. Sim, C.-S. J. J. o. V. C. Kim, and I. Representation, "Optimized contrast enhancement for real-time image and video dehazing," vol. 24, no. 3, pp. 410-425, 2013.[Cross Ref]
    [44] Q. Zhu, J. Mai, and L. J. I. t. o. i. p. Shao, "A fast single image haze removal algorithm using color attenuation prior," vol. 24, no. 11, pp. 3522-3533, 2015.[Cross Ref]

Kholud A. Karoon and Zainab. N. Nemer (2022), A Review of Methods of Removing Haze from An Image. IJEER 10(3), 742-746. DOI: 10.37391/IJEER.100354.