Đánh Giá Toàn Diện Về Phân Tích Và Triển Khai Các Phương Pháp Khử Sương Ảnh Gần Đây

Kumar R, Kaushik BK, Balasubramanian R (2017) FPGA implementation of image dehazing algorithm for real time applications. In: Proc SPIE 10396, applications of digital image processing XL. https://doi.org/10.1117/12.2274682 Narasimhan SG, Nayar SK (2002) Vision and the atmosphere. Int J Comput Vis 48:233–254 Li Y, You S, Brown MS, Tan RT (2017) Haze visibility enhancement: A Survey and quantitative benchmarking. Comput Vis Image Underst 165:1–16 Wang W, Yuan X (2017) Recent advances in image dehazing. IEEE/CAA J Automat Sin 4(3):410–436. https://doi.org/10.1109/JAS.2017.7510532 Singh D, Kumar VA (2019) Comprehensive review of computational dehazing techniques. Arch Comput Methods Eng 26:1395–1413. https://doi.org/10.1007/s11831-018-9294-z Babu GH, Venkatram N (2020) A survey on analysis and implementation of state-of-the-art haze removal techniques. J Visu Commun Image Represent 72:102912. https://doi.org/10.1016/j.jvcir.2020.102912 Das B, Ebenezer JP, Mukhopadhyay SA (2020) Comparative study of single image fog removal methods. Vis Comput. https://doi.org/10.1007/s00371-020-02010-4 https://www.ndtv.com/topic/fog-accident Min X et al (2019) Quality evaluation of image dehazing methods using synthetic hazy images. IEEE Trans Multimedia 21(9):2319–2333. https://doi.org/10.1109/TMM.2019.2902097 Shen L, Zhao Y, Peng Q, Chan JC, Kong SG (2019) An iterative image dehazing method with polarization. IEEE Trans Multimedia 21(5):1093–1107. https://doi.org/10.1109/TMM.2018.2871955 Ancuti C, Ancuti CO, De Vleeschouwer C, Bovik AC (2020) Day and night-time dehazing by local airlight estimation. IEEE Trans Image Process 29:6264–6275. https://doi.org/10.1109/TIP.2020.2988203 Chen W, Ding J, Kuo S (2019) PMS-net: Robust haze removal based on patch map for single images. In: 2019 IEEE/CVF conference on computer vision and pattern recognition (CVPR), Long Beach, CA, USA, pp 11673–11681. https://doi.org/10.1109/CVPR.2019.01195. Galdran A (2018) Image dehazing by artificial multiple-exposure image fusion. Signal Process 149:135–147 Fu X, Wang J, Zeng D, Huang Y, Ding X (2015) Remote sensing image enhancement using regularized-histogram equalization and dct. IEEE Geosci Remote Sens Lett 12(11):2301–2305 Chen BH, Huang SC, Ye JH (2015) Hazy image restoration by bi-histogram modification. ACM Tran Intell Syst Technol TIST 6(4):50 He S, Yang Q, Lau RW, Yang MH (2016) Fast weighted histograms for bilateral filtering and nearest neighbor searching. IEEE Trans Circ Syst Video Technol 26(5):891–902 Mi Z, Zhou H, Zheng Y, Wang M (2016) Single image dehazing via multi-scale gradient domain contrast enhancement. IET Image Process 10(3):206–214 Zheng L, Shi H, Gu M (2017) Infrared traffic image enhancement algorithm based on dark channel prior and gamma correction. Mod Phys Lett B 31:1740044 Gao Y, Chen H, Li H, Zhang W (2017) Single image dehazing using local linear fusion. IET Image Proc 12:637–643 Ju M, Ding C, Zhang D, Guo YJ (2018) Gamma-correction-based visibility restoration for single hazy images. IEEE Signal Process Lett 25(7):1084–1088. https://doi.org/10.1109/LSP.2018.2839580 Wang J, Lu K, Xue J, He N, Shao L (2018) Single image dehazing based on the physical model and MSRCR algorithm. IEEE Trans Circ Syst Video Technol 28(9):2190–2199. https://doi.org/10.1109/TCSVT.2017.2728822 Liu X, Zhang H, Cheung Y, You X, Tang YY (2017) Efficient single image dehazing and denoising: an efficient multi-scale correlated wavelet approach. Comput Vis Image Underst 162:23–33 Yang H, Yang CH, Tsai YJ (2020) Y-net: multi-scale feature aggregation network with wavelet structure similarity loss function for single image dehazing. In: ICASSP 2020–2020 IEEE international conference on acoustics, speech and signal processing (ICASSP), Barcelona, Spain, pp 2628–2632. https://doi.org/10.1109/ICASSP40776.2020.9053920. He J, Xing FZ, Yang R, Zhang C (2019) Fast single image dehazing via multilevel wavelet transform based optimization. arXiv:1904.08573 Singh D, Garg D, Singh Pannu H (2017) Efficient landsat image fusion using fuzzy and stationary discrete wavelet transform. Imaging Sci J 65(2):108–114 Liu C, Zhao J, Shen Y et al (2016) Texture filtering based physically plausible image dehazing. Vis Comput 32:911–920. https://doi.org/10.1007/s00371-016-1259-3 Singh D, Kumar V (2019) Image dehazing using Moore neighborhood-based gradient profile prior. Signal Process Image Commun 70:131–144 Tarel JP, Hautiere N, Cord A, Gruyer D, Halmaoui H (2010) Improved visibility of road scene images under heterogeneous fog. In: Proc IEEE Intell Veh Symp, pp 478–485 Tarel JP, Hautiere N (2009) Fast visibility restoration from a single color or gray level image. In: Proceedings of the IEEE 12th international conference on computer vision. IEEE, Kyoto, Japan, pp 2201–2208 Wang W, Yuan X, Wu X, Liu Y (2017) Fast image dehazing method based on linear transformation. IEEE Trans Multimedia 19(6):1142–1155. https://doi.org/10.1109/TMM.2017.2652069 Salazar-Colores S, Cabal-Yepez E, Ramos-Arreguin JM, Botella G, Ledesma-Carrillo LM, Ledesma S (2019) A fast image dehazing algorithm using morphological reconstruction. IEEE Trans Image Process 28(5):2357–2366. https://doi.org/10.1109/TIP.2018.2885490 Bi G, Ren J, Fu T, Nie T, Chen C, Zhang N (2017) Image dehazing based on accurate estimation of transmission in the atmospheric scattering model. IEEE Photon J 9(4):1–18. https://doi.org/10.1109/JPHOT.2017.2726107 Li Z, Zheng J (2018) Single image de-hazing using globally guided image filtering. IEEE Trans Image Process 27(1):442–450. https://doi.org/10.1109/TIP.2017.2750418 Fan X, Wang Y, Tang X, Gao R, Luo Z (2017) Two-layer Gaussian process regression with example selection for image dehazing. IEEE Trans Circuits Syst Video Technol 27(12):2505–2517. https://doi.org/10.1109/TCSVT.2016.2592328 Riaz I, Yu T, Rehman Y, Shin H (2016) Single image dehazing via reliability guided fusion. J Vis Commun Image Represent 40:85–97 Xiao J, Shen M, Lei J, Zhou J, Klette R, Sui HG (2020) Single image dehazing based on learning of haze layers. Neurocomputing 389:108–122 Jiang B, Meng H, Ma X et al (2018) Nighttime image Dehazing with modified models of color transfer and guided image filter. Multimed Tools Appl 77:3125–3141. https://doi.org/10.1007/s11042-017-4954-9 He K, Sun J, Tang X (2013) Guided image filtering. IEEE Trans Pattern Anal Mach Intell 35(6):1397–1409 Li Z, Zheng J, Zhu Z, Yao W, Wu S (2015) Weighted guided image filtering. IEEE Trans Image Process 24(1):120–129 Singh D, Kumar V, Kaur M (2019) Single image dehazing using gradient channel prior. Appl Intell 49:4276–4293. https://doi.org/10.1007/s10489-019-01504-6 Nandal S, Kumar S (2019) Single image fog removal algorithm in spatial domain using fractional order anisotropic diffusion. Multimed Tools Appl 78:10717–10732. https://doi.org/10.1007/s11042-018-6576-2 Ancuti CO, Ancuti C (2013) Single image dehazing by multi-scale fusion. IEEE Trans Image Process 22(8):3271–3282 Vazquez-Corral J, Galdran A, Cyriac P et al (2020) A fast image dehazing method that does not introduce color artifacts. J Real-Time Image Proc 17:607–622. https://doi.org/10.1007/s11554-018-0816-6 Liu P, Horng S, Lin J, Li T (2019) Contrast in haze removal: configurable contrast enhancement model based on dark channel prior. IEEE Trans Image Process 28(5):2212–2227. https://doi.org/10.1109/TIP.2018.2823424 Baig N, Riaz MM, Ghafoor A, Siddiqui AM (2016) Image dehazing using quadtree decomposition and entropy-based contextual regularization. IEEE Signal Process Lett 23(6):853–857. https://doi.org/10.1109/LSP.2016.2559805 Yuan H, Liu C, Guo Z, Sun Z (2017) A region-wised medium transmission based image dehazing method. IEEE Access 5:1735–1742 Raikwar SC, Tapaswi S (2020) Lower bound on transmission using non-linear bounding function in single image dehazing. IEEE Trans Image Process 29:4832–4847. https://doi.org/10.1109/TIP.2020.2975909 Zhang S, He F, Ren W et al (2020) Joint learning of image detail and transmission map for single image dehazing. Vis Comput 36:305–316. https://doi.org/10.1007/s00371-018-1612-9 Meng G, Wang Y, Duan J, Xiang S, Pan C (2013) Efficient image dehazing with boundary constraint and contextual regularization. In: Proceedings of the IEEE international conference on computer vision, pp 617–624 Cui T, Tian J, Wang E, Tang Y (2017) Single image dehazing by latent region-segmentation based transmission estimation and weighted L 1-norm regularization. IET Image Proc 11(2):145–154 Chen C, Do MN, Wang J (2016) Robust image and video dehazing with visual artifact suppression via gradient residual minimization. In: European conference on computer vision. Springer, pp 576–591 Wang X, Ju M, Zhang D (2017) Image haze removal via multiscale fusion and total variation. J Syst Eng Electron 28(3):597–605. https://doi.org/10.21629/JSEE.2017.03.19 Liu Q, Gao X, He L, Lu W (2018) Single image dehazing with depth-aware non-local total variation regularization. IEEE Trans Image Process 27(10):5178–5191. https://doi.org/10.1109/TIP.2018.2849928 Wu Q, Zhang J, Ren W, Zuo W, Cao X (2020) Accurate transmission estimation for removing haze and noise from a single image. IEEE Trans Image Process 29:2583–2597. https://doi.org/10.1109/TIP.2019.2949392 Park J, Han DK, Ko H (2020) Fusion of heterogeneous adversarial networks for single image dehazing. IEEE Trans Image Process 29:4721–4732. https://doi.org/10.1109/TIP.2020.2975986 Zhu Z, Wei H, Hu G, Li Y, Qi G, Mazur N (2021) A novel fast single image dehazing algorithm based on artificial multiexposure image fusion. IEEE Trans Instrum Meas 70:1–23. https://doi.org/10.1109/TIM.2020.3024335 Yuan F, Zhou Y, Xia X, Shi J, Fang Y, Qian X (2020) Image dehazing based on a transmission fusion strategy by automatic image matting. Comput Vis Image Underst 194:102933 Ma Z, Wen J, Zhang C, Liu Q, Yan D (2016) An effective fusion defogging approach for single sea fog image. Neuro-computing 173:1257–1267 Son C, Zhang X (2018) Near-infrared fusion via color regularization for haze and color distortion removals. IEEE Trans Circuits Syst Video Technol 28(11):3111–3126. https://doi.org/10.1109/TCSVT.2017.2748150 Shibata T, Tanaka M, Okutomi M (2019) Unified image fusion framework with learning-based application-adaptive importance measure. IEEE Trans Comput Imaging 5(1):82–96. https://doi.org/10.1109/TCI.2018.2879021 Zhao D, Xu L, Yan Y, Chen J, Duan L-Y (2019) Multi-scale optimal fusion model for single image dehazing. Signal Process 74:253–265 Agrawal SC, Jalal AS (2021) A joint cumulative distribution function and gradient fusion-based method for dehazing of long shot hazy images. J Vis Commun Image Represent 77:103087 He K, Sun J, Tang X (2010) Single image haze removal using dark channel prior. IEEE Trans Pattern Anal Mach Intell 33(12):2341–2353 Zhu Q, Mai J, Shao L et al (2015) A fast single image haze removal algorithm using color attenuation prior. TIP 24(11):3522–3533 Zhenfei Gu, Mingye Ju, Zhang D (2017) A single image dehazing method using average saturation prior. Math Probl Eng. https://doi.org/10.1155/2017/6851301 Berman D, Treibitz T, Avidan S (2020) Single image dehazing using haze-lines. IEEE Trans Pattern Anal Mach Intel 42(3):720–734. https://doi.org/10.1109/TPAMI.2018.2882478 Bui TM, Kim W (2018) Single image dehazing using color ellipsoid prior. IEEE Trans Image Process 27(2):999–1009. https://doi.org/10.1109/TIP.2017.2771158 Mei K, Jiang A, Li J, Li J, Wang M (2019) Progressive feature fusion network for realistic image dehazing. In: Asian conference on computer vision. https://doi.org/10.1007/978-3-030-20887-5_13 Salazar-Colores S, Ramos-Arreguín JM, Pedraza-Ortega JC et al (2019) Efficient single image dehazing by modifying the dark channel prior. J Image Video Proc 2019:66. https://doi.org/10.1186/s13640-019-0447-2 Zhang L, Wang S, Wang X (2018) Saliency-based dark channel prior model for single image haze removal. IET Image Process 12(6):1049–1055 Zhu M, He B, Wu Q (2018) Single image dehazing based on dark channel prior and energy minimization. IEEE Signal Process Lett 25(2):174–178. https://doi.org/10.1109/LSP.2017.2780886 Shiau Y, Yang H, Chen P, Chuang Y (2013) Hardware implementation of a fast and efficient haze removal method. IEEE Trans Circ Syst Video Technol 23(8):1369–1374. https://doi.org/10.1109/TCSVT.2013.2243650 Ren W, Liu S, Zhang H, Pan J, Cao X, Yang M-H (2016) Single image dehazing via multi-scale convolutional neural networks. In: ECCV, 2016 Cai B, Xu X, Jia K, Qing C, Tao D (2016) Dehazenet: an end-to-end system for single image haze removal. IEEE Trans Image Process 25(11):5187–5198 Li B, Peng X, Wang Z, Xu J, Feng D (2017) Aod-net: all-in-one dehazing network. In: Proceedings of the IEEE international conference on computer vision, pp 4770–4778 Engin D, Genc A, Ekenel HK (2018) Cycle-dehaze: enhanced CycleGAN for single image dehazing. In: 2018 IEEE/CVF conference on computer vision and pattern recognition workshops (CVPRW), Salt Lake City, UT, pp 938–9388. https://doi.org/10.1109/CVPRW.2018.00127. Ren W, Ma L, Zhang J, Pan J, Cao X, Liu W, Yang M-H (2018) Gated fusion network for single image dehazing. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3253–3261 Liu Z, Xiao B, Alrabeiah M, Wang K, Chen J (2019) Single image dehazing with a generic model-agnostic convolutional neural network. IEEE Signal Process Lett 26(6):833–837 Singh A, Bhave A, Prasad DK (2020) Single image dehazing for a variety of haze scenarios using back projected pyramid network. In: European conference on computer vision workshops Gandelsman Y, Shocher A, Irani M (2019) Double-DIP: unsupervised image decomposition via coupled deepimage-priors. In: CVPR Li B, Gou Y, Liu JZ, Zhu H, Zhou JT, Peng X (2020) Zero-shot image dehazing. IEEE Trans Image Process 29:8457–8466. https://doi.org/10.1109/TIP.2020.3016134 Liu Y, Pan J, Ren J, Su Z (2019) Learning deep priors for image dehazing. In: Proceedings of the IEEE/CVF international conference on computer vision (ICCV), pp 2492–2500 Zhang H, Sindagi V, Patel VM (2020) Joint transmission map estimation and dehazing using deep networks. IEEE Trans Circ Syst Video Technol 30(7):1975–1986 Chen D, He M, Fan Q, Liao J, Zhang L, Hou D, Yuan L, Hua G (2019) Gated context aggregation network for image dehazing and deraining. In: 2019 IEEE winter conference on applications of computer vision (WACV), pp 1375–1383 Zhang H, Sindagi V, Patel VM (2018) Multi-scale single image dehazing using perceptual pyramid deep network. In: 2018 IEEE/CVF conference on computer vision and pattern recognition workshops (CVPRW), Salt Lake City, UT, pp 1015–101509. https://doi.org/10.1109/CVPRW.2018.00135. Qin X, Wang Z, Bai Y, Xie X, Jia H (2019) Ffa-net: feature fusion attention network for single image dehazing. arXiv:1911.07559 Li L, Dong Y, Ren W, Pan J, Gao C, Sang N, Yang MH (2019) Semi-supervised image dehazing. IEEE Trans Image Process. https://doi.org/10.1109/TIP.2019.2952690 Golts A, Freedman D, Elad M (2020) Unsupervised single image dehazing using dark channel prior loss. IEEE Trans Image Process 29:2692–2701. https://doi.org/10.1109/TIP.2019.2952032 Agrawal SC, Jalal AS (2022) Distortion-free image dehazing by superpixels and ensemble neural network. Vis Comput 38:781–796. https://doi.org/10.1007/s00371-020-02049-3 Yu M, Cherukuri V, Guo T, Monga V (2020) Ensemble dehazing networks for non-homogeneous haze. In: 2020 IEEE/CVF conference on computer vision and pattern recognition workshops (CVPRW), Seattle, WA, USA, pp 1832–1841. https://doi.org/10.1109/CVPRW50498.2020.00233. Zhang S, Wu Y, Zhao Y, Cheng Z, Ren W (2020) Color-Constrained Dehazing Model. In: 2020 IEEE/CVF conference on computer vision and pattern recognition workshops (CVPRW), Seattle, WA, USA, pp 3799–3807. https://doi.org/10.1109/CVPRW50498.2020.00443. Golts A, Freedman D, Elad M Deep-energy: unsupervised training of deep neural networks. https://arxiv.org/abs/1805.12355 Li B, Gou Y, Gu S, Liu JZ, Zhou JT, Peng X (2020) You only look yourself: Unsupervised and untrained single image dehazing neural network. http://arxiv.org/abs/2006.16829 Metwaly K, Li X, Guo T, Monga V (2020) NonLocal channel attention for nonhomogeneous image dehazing. 2020 IEEE/CVF conference on computer vision and pattern recognition workshops (CVPRW), Seattle, WA, USA, pp 1842–1851. https://doi.org/10.1109/CVPRW50498.2020.00234. Wu H, Liu J, Xie Y, Qu Y, Ma L (2020) Knowledge transfer dehazing network for non-homogeneous dehazing. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (CVPR) workshops, pp 478–479 Tarel J, Hautiere N, Caraffa L, Cord A, Halmaoui H, Gruyer D (2012) Vision enhancement in homogeneous and heterogeneous fog. IEEE Intel Transport Syst Mag 4(2):6–20. https://doi.org/10.1109/MITS.2012.2189969 Fattal R (2014) Dehazing using color-lines. ACM Trans Graph 34(1):13 Ma K, Liu W, Wang Z (2015) Perceptual evaluation of single image dehazing algorithms. In: 2015 IEEE international conference on image processing (ICIP), Quebec City, QC, pp 3600–3604. https://doi.org/10.1109/ICIP.2015.7351475. Choi LK, You J, Bovik AC (2015) Referenceless prediction of perceptual fog density and perceptual image defogging. IEEE Trans Image Process 24(11):3888–3901. https://doi.org/10.1109/TIP.2015.2456502 Ancuti C, Ancuti CO, De Vleeschouwer C (2016) D-HAZY: a dataset to evaluate quantitatively dehazing algorithms. In: 2016 IEEE international conference on image processing (ICIP), Phoenix, AZ, pp 2226–2230. https://doi.org/10.1109/ICIP.2016.7532754. Lee Y-H, Tang S-J (2021) A Design of Image Dehazing Engine Using DTE and DAE Techniques. IEEE Trans Circ Syst Video Technol. https://doi.org/10.1109/TCSVT.2020.3034250 Sakaridis C, Dai D, Van Gool L (2017) Semantic foggy scene understanding with synthetic data. arXiv:1708.07819 Zhang Y, Ding L, Sharma G (2017) Hazerd: an outdoor scene dataset and benchmark for single image dehazing. In: 2017 IEEE international conference on image processing (ICIP). IEEE, pp 3205–3209 Ancuti CO, Ancuti C, Timofte R, De Vleeschouwer C (2018) I-HAZE: a dehazing benchmark with real hazy and haze-free indoor images. ArXiv e-prints Ancuti CO, Ancuti C, Timofte R, De Vleeschouwer C (2018) O-HAZE: a dehazing benchmark with real hazy and haze-free outdoor images. In: 2018 IEEE/CVF conference on computer vision and pattern recognition workshops (CVPRW), Salt Lake City, UT, pp 867–8678. https://doi.org/10.1109/CVPRW.2018.00119. Ancuti CO, Ancuti C, Sbert M, Timofte R (2019) Dense haze: a benchmark for image dehazing with dense-haze and haze-free images. In: IEEE international conference on image processing (ICIP) Li B et al (2019) Benchmarking single-image dehazing and beyond. IEEE Trans Image Process 28(1):492–505. https://doi.org/10.1109/TIP.2018.2867951 Ancuti CO, Ancuti C, Timofte R (2020) NH-HAZE: an image dehazing benchmark with non-homogeneous hazy and haze-free images. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition workshops, pp 444–445 Borkar K, Mukherjee S (2020) Single image dehazing by approximating and eliminating the additional airlight component. Neurocomputing 400:294–308 Hautiere N, Tarel JP, Aubert D, Dumont E (2008) Blind contrast enhancement assessment by gradient ratioing at visible edges. Image Anal Stereol J 27(2):87–95 Zhan Y, Zhang R (2017) No-reference JPEG image quality assessment based on blockiness and luminance change. IEEE Signal Process Lett 24(6):760–764. https://doi.org/10.1109/LSP.2017.2688371 Crete-Roffet F, Dolmiere T, Ladret P, Nicolas M (2007) The blur effect: perception and estimation with a new no-reference perceptual blur metric. In: SPIE Saad MA, Bovik AC, Charrier C (2012) Blind image quality assessment: a natural scene statistics approach in the DCT domain. IEEE Trans Image Process 21(8):3339–3352. https://doi.org/10.1109/TIP.2012.2191563 Mittal A, Moorthy AK, Bovik AC (2012) No-reference image quality assessment in the spatial domain. IEEE Trans Image Process 21(12):4695–4708 Mittal A, Soundararajan R, Bovik AC (2013) Making a “completely blind” image quality analyzer. IEEE Signal Process Lett 20(3):209–212. https://doi.org/10.1109/LSP.2012.2227726 Min X, Zhai G, Gu K, Yang X, Guan X (2019) Objective quality evaluation of dehazed images. IEEE Trans Intell Transport Syst 20(8):2879–2892. https://doi.org/10.1109/TITS.2018.2868771 Zhang R, Isola P, Efros AA, Shechtman E, Wang O (2018) The unreasonable effectiveness of deep features as a perceptual metric. In: Proc CVPR Luan Z, Shang Y, Zhou X, Shao Z, Guo G, Liu X (2017) Fast single image dehazing based on a regression model. Neurocomputing 245:10–22 Wang Z, Bovik AC (2006) Modern image quality assessment. Synth Lect Image Video Multimedia Process. https://doi.org/10.2200/S00010ED1V01Y200508IVM003 Wang Z, Bovik AC, Sheikh HR, Simoncelli EP (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600–612 Sharma G, Wu W, Dalal E (2005) The ciede2000 color difference formula: Implementation notes, supplementary test data, and mathematical observations. Color Res Appl. https://doi.org/10.1002/col.20070 Westland S, Ripamonti C, Cheung V (2005) Computational colour science using matlab, 2nd edn. Wiley, New York Shi L et al (Sept. 2018) Removing haze particles from single image via exponential inference with support vector data description. IEEE Trans Multimedia 20(9):2503–2512. https://doi.org/10.1109/TMM.2018.2807593 Sharma P, Jain P, Sur A (2020) Scale-aware conditional generative adversarial network for image dehazing. In: Proceedings of the IEEE/CVF winter conference on applications of computer vision (WACV), pp 2355–2365 https://timesofindia.indiatimes.com/india/over-10000-lives-lost-in-fog-related-road-crashes/articleshow/67391588.cms Santra S, Mondal R, Chanda B (2018) Learning a patch quality comparator for single image dehazing. IEEE Trans Image Process 27(9):4598–4607. https://doi.org/10.1109/TIP.2018.2841198 Yang D, Sun J (2018) Proximal dehaze-net: a prior learning-based deep network for single image dehazing. In: ECCV, pp 702–717 Deng Z, Zhu L, Hu X, Fu C-W, Xu X, Zhang Q, Qin J, Heng P-A (2019) Deep multi-model fusion for single-image dehazing. In: Proceedings of the IEEE/CVF international conference on computer vision (ICCV), pp 2453–2462 Bianco S, Celona L, Piccoli F, Schettini R (2019) High-resolution single image dehazing using encoder-decoder architecture. In: 2019 IEEE/CVF conference on computer vision and pattern recognition workshops (CVPRW), Long Beach, CA, USA, pp 1927–1935. https://doi.org/10.1109/CVPRW.2019.00244. Agrawal SC, Jalal AS (2022) Dense haze removal by nonlinear transformation. IEEE Trans Circuits Syst Video Technol 32(2):593–607. https://doi.org/10.1109/TCSVT.2021.3068625 Zhang B, Zhao J (2017) Hardware implementation for real-time haze removal”. IEEE Trans Very Large Scale Integr Syst 25(3):1188–1192 Shiau Y-H, Kuo Y-T, Chen P-Y, Hsu F-Y (2019) VLSI design of an efficient flicker-free video defogging method for real-time applications. IEEE Trans Circuits Syst Video Technol 29(1):238–251 Kumar R, Balasubramanian R, Kaushik BK (2020) Efficient method and architecture for real-time video defogging. IEEE Trans Intell Transp Syst. https://doi.org/10.1109/TITS.2020.2993906 Salazar-Colores S, Cruz-Aceves I, Ramos-Arreguin J (2018) Single image dehazing using a multilayer perceptron. J Electron Imaging. https://doi.org/10.1117/1.JEI.27.4.043022 Zhu Y, Tang G, Zhang X, Jiang J, Tian Q (2018) Haze removal method for natural restoration of images with sky. Neurocomputing 275:499–510 Ju M, Ding C, Ren W, Yang Y, Zhang D, Guo YJ (2021) IDE: image dehazing and exposure using an enhanced atmospheric scattering model. IEEE Trans Image Process 30:2180–2192. https://doi.org/10.1109/TIP.2021.3050643 Sahu G, Seal A, Krejcar O, Yazidi A (2021) Single image dehazing using a new color channel. J Visual Commun Image Represent 74:103008 Ju M, Ding C, Guo YJ, Zhang D (2020) IDGCP: image dehazing based on gamma correction prior. IEEE Trans Image Process 29:3104–3118. https://doi.org/10.1109/TIP.2019.2957852 Morales P, Klinghoffer T, Lee SJ (2019) Feature forwarding for efficient single image dehazing. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (CVPR) workshops Zheng X, et al. (2018) Strong baseline for single image dehazing with deep features and instance normalization. In: BMVC Yang A, Wang H, Ji Z, Pang Y, Shao L (2019) Dual-path in dual-path network for single image dehazing. In: Proceedings of the twenty-eighth international joint conference on artificial intelligence main track, pp 4627–4634. https://doi.org/10.24963/ijcai.2019/643 Zhang H, Patel VM (2018) Densely connected pyramid dehazing network. In: CVPR, pp 3194–3203 Galdran A, Vazquez-Corral J, Pardo D, Bertalmío M (2017) Fusion-based variational image dehazing. IEEE Signal Process Lett 24(2):151–155. https://doi.org/10.1109/LSP.2016.2643168 Zheng M, Qi G, Zhu Z, Li Y, Wei H, Liu Y (2020) Image dehazing by an artificial image fusion method based on adaptive structure decomposition. IEEE Sens J 20(14):8062–8072. https://doi.org/10.1109/JSEN.2020.2981719 Gao Y, Su Y, Li Q, Li H, Li J (2020) Single image dehazing via self-constructing image fusion. Signal Process 167:107284 Wang B, Wei B, Kang Z et al (2020) Fast color balance and multi-path fusion for sandstorm image enhancement. SIViP. https://doi.org/10.1007/s11760-020-01786-1 Huo F, Zhu X, Zeng H, Liu Q, Qiu J (2021) Fast fusion-based dehazing with histogram modification and improved atmospheric illumination prior. IEEE Sens J 21(4):5259–5270. https://doi.org/10.1109/JSEN.2020.3033713 Hong S, Kim M, Kang MG (2021) Single image dehazing via atmospheric scattering model-based image fusion. Signal Process 178:107798 Wang R, Li R, Sun H (2016) Haze removal based on multiple scattering model with superpixel algorithm. Signal Process 127:24–36 Jiang Y, Sun C, Zhao Y, Yang L (2017) Image dehazing using adaptive bi-channel priors on superpixels. Comput Vis Image Understand 165:17–32 Yang M, Liu J, Li Z (2018) Superpixel-based single nighttime image haze removal. IEEE Trans Multimedia 20(11):3008–3018. https://doi.org/10.1109/TMM.2018.2820327 Wang P, Fan Q, Zhang Y, Bao F, Zhang C (2019) A novel dehazing method for color fidelity and contrast enhancement on mobile devices. IEEE Trans Consum Electron 65(1):47–56. https://doi.org/10.1109/TCE.2018.2884794 Hassan H, Bashir AK, Ahmad M et al (2020) Real-time image dehazing by superpixels segmentation and guidance filter. J Real-Time Image Proc. https://doi.org/10.1007/s11554-020-00953-4 Wang LZSWX (2021) Single image dehazing based on bright channel prior model and saliency analysis strategy. IET Image Proc 15(3):1023–1031 Tan Y, Wang G (2020) Image haze removal based on superpixels and Markov random field. IEEE Access 8:60728–60736. https://doi.org/10.1109/ACCESS.2020.2982910 Yuan F, Huang H (2018) Image haze removal via reference retrieval and scene prior. IEEE Trans Image Process 27(9):4395–4409. https://doi.org/10.1109/TIP.2018.2837900 Mandal S, Rajagopalan AN (2020) Local proximity for enhanced visibility in haze. IEEE Trans Image Process 29:2478–2491 Reda M, Zhao Y, Chan JC-W (2017) polarization guided autoregressive model for depth recovery. IEEE Photon J 9(3):1–16 Haofeng Hu, Zhao L, Li X, Wang H, Yang J, Li K, Liu T (2018) Polarimetric image recovery in turbid media employing circularly polarized light. Opt Express 26:25047–25059 Li X et al (2019) Pseudo-polarimetric method for dense haze removal. IEEE Photon J 11(1):1–11. https://doi.org/10.1109/JPHOT.2018.2890771 Tian Y, Liu B, Su X, Wang L, Li K (2019) Underwater imaging based on LF and polarization. IEEE Photon J 11(1):1–9. https://doi.org/10.1109/JPHOT.2018.2890286 Liang Z, Ding X, Mi Z, Wang Y, Fu X (2022) Effective polarization-based image dehazing with regularization constraint”. IEEE Geosci Remote Sens Lett. https://doi.org/10.1109/LGRS.2020.3023805 Zhang L, Yin Z, Zhao K, Tian H (2020) Lane detection in dense fog using a polarimetric dehazing method. Appl Opt 59:5702–5707 Kim SE, Park TH, Eom IK (2020) Fast single image dehazing using saturation based transmission map estimation. IEEE Trans Image Process 29:1985–1998. https://doi.org/10.1109/TIP.2019.2948279 Lu Z, Long B, Yang S (2020) Saturation based iterative approach for single image dehazing. IEEE Signal Process Lett 27:665–669. https://doi.org/10.1109/LSP.2020.2985570 Gao Y, Hu H, Li B, Guo Q, Pu S (2019) Detail preserved single image dehazing algorithm based on airlight refinement. IEEE Trans Multimedia 21(2):351–362. https://doi.org/10.1109/TMM.2018.2856095 Wang A, Wang W, Liu J, Gu N (2019) AIPNet: image-to-image single image dehazing with atmospheric illumination prior. IEEE Trans Image Process 28(1):381–393. https://doi.org/10.1109/TIP.2018.2868567 Hu H, Zhang H, Zhao Z, Li B, Zheng J (2020) Adaptive single image dehazing using joint local-global illumination adjustment. IEEE Trans Multimedia 22(6):1485–1495. https://doi.org/10.1109/TMM.2019.2944260 Dhara SK, Roy M, Sen D, Biswas PK (2021) Color cast dependent image dehazing via adaptive airlight refinement and non-linear color balancing. IEEE Trans Circ Syst Video Technol. https://doi.org/10.1109/TCSVT.2020.3007850 Lee Y, Wu B (2019) Algorithm and architecture design of a hardware-efficient image dehazing engine. IEEE Trans Circuits Syst Video Technol 29(7):2146–2161. https://doi.org/10.1109/TCSVT.2018.2862906 Kumar R, Kaushik BK, Balasubramanian R (2019) Multispectral transmission map fusion method and architecture for image dehazing. IEEE Trans Very Large-Scale Integr Syst 27(11):2693–2697 Soma P, Jatoth RK (2020) Implementation of a novel, fast and efficient image de-hazing algorithm on embedded hardware platforms. Circuits Syst Signal Process. https://doi.org/10.1007/s00034-020-01517-4 Wu X, Wang K, Li Y, Liu K, Huang B (2021) Accelerating haze removal algorithm using CUDA. Remote Sens 13(1):85. https://doi.org/10.3390/rs13010085 Xie CH, Qiao WW, Liu Z et al (2017) Single image dehazing using kernel regression model and dark channel prior. SIViP 11:705–712. https://doi.org/10.1007/s11760-016-1013-3 Chen B, Huang S, Li C, Kuo S (2018) Haze removal using radial basis function networks for visibility restoration applications. IEEE Trans Neural Netw Learn Syst 29(8):3828–3838. https://doi.org/10.1109/TNNLS.2017.2741975 Kang C, Kim G (2018) Single image haze removal method using conditional random fields. IEEE Signal Process Lett 25(6):818–822. https://doi.org/10.1109/LSP.2018.2827882 Yin JL, Huang YC, Chen BH, Ye SZ (2020) Color transferred convolutional neural networks for image dehazing. IEEE Trans Circuits Syst Video Technol 30(11):3957–3967. https://doi.org/10.1109/TCSVT.2019.2917315 Chaitanya BSNV, Mukherjee S (2021) Single image dehazing using improved cycleGAN. J Visual Commun Image Represent 74:103014 Li Y, Liu Y, Yan Q, Zhang K (2021) Deep dehazing network with latent ensembling architecture and adversarial learning. IEEE Trans Image Process 30:1354–1368. https://doi.org/10.1109/TIP.2020.3044208 Sun Z, Zhang Y, Bao F, Shao K, Liu X, Zhang C (2021) ICycleGAN: Single image dehazing based on iterative dehazing model and CycleGAN. Comput Vis Image Understand 203:1031332 . Huang L, Yin J, Chen B, Ye S (2019) Towards unsupervised single image dehazing with deep learning. In: 2019 IEEE international conference on image processing (ICIP), Taipei, Taiwan, pp 2741–2745. https://doi.org/10.1109/ICIP.2019.8803316. Liu R, Ma L, Wang Y, Zhang L (2019) Learning converged propagations with deep prior ensemble for image enhancement. IEEE Trans Image Process 28(3):1528–1543. https://doi.org/10.1109/TIP.2018.2875568 Das SD, Dutta S (2020) Fast deep multi-patch hierarchical network for nonhomogeneous image dehazing. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (CVPR) workshops, pp 482–483 Mehta A, Sinha H, Mandal M, Narang P (2021) Domain-aware unsupervised hyperspectral reconstruction for aerial image dehazing. In: Proceedings of the IEEE/CVF winter conference on applications of computer vision (WACV), pp 413–422 Mehta A, Sinha H, Narang P, Murari (2020) HIDEGAN: a hyperspectral-guided image Dehazing GAN Mandal. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (CVPR) workshops, pp 212–213 Dudhane A, Murala S (2020) RYF-net: deep fusion network for single image haze removal. IEEE Trans Image Process 29:628–640. https://doi.org/10.1109/TIP.2019.2934360