4.11.2.8.2 Fog Removal, Defogging

Chapter Contents (Back)
Fog. Defogging.
See also General Weather Enhancement, Restoration. Driving:
See also Fog, Fog Detection, Mist, Visibility, Driver Assistance.

Nishino, K.[Ko], Kratz, L.[Louis], Lombardi, S.[Stephen],
Bayesian Defogging,
IJCV(98), No. 3, July 2012, pp. 263-278.
WWW Link. 1202
BibRef

Gibson, K.B.[Kristofor B.], Nguyen, T.Q.[Truong Q.],
An Analysis of Single Image Defogging Methods using a Color Ellipsoid Framework,
JIVP(2013), No. 1, 2013, pp. 37.
DOI Link 1307
BibRef
Earlier:
Hazy image modeling using color ellipsoids,
ICIP11(1861-1864).
IEEE DOI 1201
BibRef

Gibson, K.B.[Kristofor B.], Nguyen, T.Q.[Truong Q.],
A No-Reference Perceptual Based Contrast Enhancement Metric for Ocean Scenes in Fog,
IP(22), No. 10, 2013, pp. 3982-3993.
IEEE DOI 1309
AdaBoost, Contrast enhancement metric BibRef

Wang, Y., Fan, C.,
Single Image Defogging by Multiscale Depth Fusion,
IP(23), No. 11, November 2014, pp. 4826-4837.
IEEE DOI 1410
Adaptation models BibRef

Guo, J.M.[Jing-Ming], Syue, J.Y.[Jin-Yu], Radzicki, V.R.[Vincent R.], Lee, H.[Hua],
An Efficient Fusion-Based Defogging,
IP(26), No. 9, September 2017, pp. 4217-4228.
IEEE DOI 1708
image enhancement, image fusion, Gaussian-based dark channel method, atmospheric light, flicker-free module, flickering effect reduction, frame-based dehazing process, fusion weighting scheme, fusion-based defogging, BibRef

Lee, Y., Hirakawa, K., Nguyen, T.Q.,
Joint Defogging and Demosaicking,
IP(26), No. 6, June 2017, pp. 3051-3063.
IEEE DOI 1705
Digital cameras, Image restoration, Image sensors, Pipelines, Scattering, Defogging, dehazing, demosaicking, digital camera processing pipeline, image restoration, image, sensor, noise BibRef

Qu, C.[Chen], Bi, D.[Duyan],
Novel Defogging Algorithm Based on the Joint Use of Saturation and Color Attenuation Prior,
IEICE(E101-D), No. 5, May 2018, pp. 1421-1429.
WWW Link. 1805
BibRef

Mutimbu, L.[Lawrence], Robles-Kelly, A.[Antonio],
A factor graph evidence combining approach to image defogging,
PR(82), 2018, pp. 56-67.
Elsevier DOI 1806
Factor graphs, Evidence combining, Simplicial spanning tree, Procrustes transformation, Maximum a-posteriori inference, Image defogging BibRef

Ling, Z., Gong, J., Fan, G., Lu, X.,
Optimal Transmission Estimation via Fog Density Perception for Efficient Single Image Defogging,
MultMed(20), No. 7, July 2018, pp. 1699-1711.
IEEE DOI 1806
Atmospheric modeling, Computational modeling, Degradation, Image color analysis, Mathematical model, Meteorology, Scattering, optimal transmission model BibRef

Shiau, Y., Kuo, Y., Chen, P., Hsu, F.,
VLSI Design of an Efficient Flicker-Free Video Defogging Method for Real-Time Applications,
CirSysVideo(29), No. 1, January 2019, pp. 238-251.
IEEE DOI 1901
Streaming media, Algorithm design and analysis, Real-time systems, Heuristic algorithms, Atmospheric modeling, VLSI BibRef

Hu, H., Guo, Q., Zheng, J., Wang, H., Li, B.,
Single Image Defogging Based on Illumination Decomposition for Visual Maritime Surveillance,
IP(28), No. 6, June 2019, pp. 2882-2897.
IEEE DOI 1905
aerosols, brightness, fog, image colour analysis, image enhancement, image restoration, image sensors, lighting, marine engineering, atmospheric aerosol model BibRef

Tufail, Z.[Zahid], Khurshid, K.[Khawar], Salman, A.[Ahmad], Khurshid, K.[Khurram],
Optimisation of transmission map for improved image defogging,
IET-IPR(13), No. 7, 30 May 2019, pp. 1161-1169.
DOI Link 1906
BibRef

Liu, W.[Wei], Yao, R.G.[Rong-Guo], Qiu, G.P.[Guo-Ping],
A Physics Based Generative Adversarial Network for Single Image Defogging,
IVC(92), 2019, pp. 103815.
Elsevier DOI 1912
Single image defogging, Image restoration, Image enhancement, CycleGAN, Subjective evaluation BibRef

Nandal, S.[Savita], Kumar, S.[Sanjeev],
Fractional-Order Anisotropic Diffusion for Defogging of RGB Images,
IJIG(20), No. 1 2020, pp. 2050001.
DOI Link 2002
BibRef

Shi, Y.H.[Yong-Hua], Jiang, X.[Xishun],
Deep quality assessment toward defogged aerial images,
SP:IC(83), 2020, pp. 115808.
Elsevier DOI 2003
Image defogging, Image quality, Aerial image, Adversarial network, Random forest BibRef

Hassan, N.[Najmul], Ullah, S.[Sami], Bhatti, N.[Naeem], Mahmood, H.[Hasan], Zia, M.[Muhammad],
A cascaded approach for image defogging based on physical and enhancement models,
SIViP(14), No. 5, July 2020, pp. 867-875.
Springer DOI 2006
BibRef

Liu, W.[Wei], Hou, X.X.[Xian-Xu], Duan, J.[Jiang], Qiu, G.P.[Guo-Ping],
End-to-End Single Image Fog Removal Using Enhanced Cycle Consistent Adversarial Networks,
IP(29), 2020, pp. 7819-7833.
IEEE DOI 2007
Single image defogging, cycleGAN, unpaired training, image restoration BibRef

Kim, D.[Donghee], Park, M.S.[Myung-Sook], Park, Y.J.[Young-Je], Kim, W.[Wonkook],
Geostationary Ocean Color Imager (GOCI) Marine Fog Detection in Combination with Himawari-8 Based on the Decision Tree,
RS(12), No. 1, 2020, pp. xx-yy.
DOI Link 2001
BibRef

Zaghloul, R.I.[Rawan I.], Hiary, H.[Hazem],
A Fast Single Image Fog Removal Method Using Geometric Mean Histogram Equalization,
IJIG(21), No. 1 2021, pp. 2150001.
DOI Link 2102
BibRef

Yang, Y.L.[Yu-Liang], Long, W.[Wei], Li, Y.Y.[Yan-Yan], Shi, X.Q.[Xiao-Qiu], Gao, L.[Lin],
Image defogging based on amended dark channel prior and 4-directional L1 regularisation,
IET-IPR(15), No. 11, 2021, pp. 2454-2477.
DOI Link 2108
BibRef

Zhu, Z.Q.[Zhi-Qin], Luo, Y.Q.[Ya-Qin], Qi, G.Q.[Guan-Qiu], Meng, J.[Jun], Li, Y.[Yong], Mazur, N.[Neal],
Remote Sensing Image Defogging Networks Based on Dual Self-Attention Boost Residual Octave Convolution,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
From aerial images. BibRef

Ronen, A.[Ayala], Tzadok, T.[Tamir], Rostkier-Edelstein, D.[Dorita], Agassi, E.[Eyal],
Fog Measurements with IR Whole Sky Imager and Doppler Lidar, Combined with In Situ Instruments,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Kumar, R.[Rahul], Balasubramanian, R.[Raman], Kaushik, B.K.[Brajesh Kumar],
Efficient Method and Architecture for Real-Time Video Defogging,
ITS(22), No. 10, October 2021, pp. 6536-6546.
IEEE DOI 2110
Estimation, Hardware, Image restoration, Real-time systems, Streaming media, Memory management, Defogging, dehazing, video processing BibRef

Arif, Z.H.[Zainab Hussein], Mahmoud, M.A.[Moamin A.], Abdulkareem, K.H.[Karrar Hameed], Mohammed, M.A.[Mazin Abed], Al-Mhiqani, M.N.[Mohammed Nasser], Mutlag, A.A.[Ammar Awad], Damaševicius, R.[Robertas],
Comprehensive Review of Machine Learning (ML) in Image Defogging: Taxonomy of Concepts, Scenes, Feature Extraction, and Classification techniques,
IET-IPR(16), No. 2, 2022, pp. 289-310.
DOI Link 2201
BibRef

Chen, T.[Ting], Liu, M.[Mengni], Gao, T.[Tao], Cheng, P.[Peng], Mei, S.H.[Shao-Hui], Li, Y.H.[Yong-Hui],
A Fusion-Based Defogging Algorithm,
RS(14), No. 2, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Cui, Y.[Yani], Zhi, S.[Shuaiqing], Liu, W.J.[Wen-Jin], Deng, J.X.[Jia-Xian], Ren, J.[Jia],
An improved dark channel defogging algorithm based on the HSI colour space,
IET-IPR(16), No. 3, 2022, pp. 823-838.
DOI Link 2202
BibRef

Chen, W.T.[Wei-Ting], Lou, H.L.[Hao-Lun], Fang, H.Y.[Hao-Yu], Chen, I.H.[I-Hsiang], Chen, Y.W.[Yi-Wen], Ding, J.J.[Jian-Jiun], Kuo, S.Y.[Sy-Yen],
DesmokeNet: A Two-Stage Smoke Removal Pipeline Based on Self-Attentive Feature Consensus and Multi-Level Contrastive Regularization,
CirSysVideo(32), No. 6, June 2022, pp. 3346-3359.
IEEE DOI 2206
Image color analysis, Pipelines, Surgery, Image reconstruction, Optical losses, Laparoscopes, Heuristic algorithms, multi-level contrastive regularization BibRef

Pikun, W.[Wang], Ling, W.[Wu], Jiang-Xin, Q.[Qi], Jiashuai, D.[Dai],
Unmanned aerial vehicles object detection based on image haze removal under sea fog conditions,
IET-IPR(16), No. 10, 2022, pp. 2709-2721.
DOI Link 2207
BibRef

Xu, L.[Linli], Liang, P.X.[Pei-Xian], Han, J.[Jing], Bai, L.[Lianfa], Chen, D.Z.[Danny Z.],
Global Filter of Fusing Near-Infrared and Visible Images in Frequency Domain for Defogging,
SPLetters(29), 2022, pp. 1953-1957.
IEEE DOI 2209
Image color analysis, Scattering, Atmospheric modeling, Distortion, Imaging, Frequency-domain analysis, Attenuation, NIR and VIS images fusion BibRef

Shi, W.P.[Wei-Peng], Qin, W.[Wenhu], Chen, A.[Allshine],
Towards Robust Semantic Segmentation of Land Covers in Foggy Conditions,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Wang, Z.Q.[Zi-Quan], Zhang, Y.S.[Yong-Sheng], Zhang, Z.C.[Zhen-Chao], Jiang, Z.P.[Zhi-Peng], Yu, Y.[Ying], Li, L.[Li], Zhang, L.[Lei],
SDAT-Former++: A Foggy Scene Semantic Segmentation Method with Stronger Domain Adaption Teacher for Remote Sensing Images,
RS(15), No. 24, 2023, pp. 5704.
DOI Link 2401
BibRef
Earlier: A1, A2, A5, A4, Only:
SDAT-Former: Foggy Scene Semantic Segmentation Via A Strong Domain Adaptation Teacher,
ICIP23(1760-1764)
IEEE DOI 2312
BibRef

Li, L.[Linge], Liu, X.Q.[Xiao-Qin], Shi, F.Y.[Fei-Yu], Cai, Y.H.[Yi-Hua], Zhang, Y.[Ying], Fang, P.[Ping], Mu, C.[Chao], Weng, N.Q.[Ning-Quan],
Foggy image restoration using deep sub-pixel reconstruction network,
IET-IPR(18), No. 3, 2024, pp. 707-721.
DOI Link 2402
fog, image reconstruction, image restoration BibRef


Zhong, M.Q.[Mian-Qing], Wang, X.[Xue], Wang, J.[Jun], Kang, J.M.[Jun-Mei],
A Remote Sensing Image Defogging Method Based on Improved CycleGAN Network,
CVIDL23(113-116)
IEEE DOI 2403
Deep learning, Satellites, Image resolution, Computational modeling, Training data, Sensors, image dehazing, CycleGAN BibRef

Ramazzina, A.[Andrea], Bijelic, M.[Mario], Walz, S.[Stefanie], Sanvito, A.[Alessandro], Scheuble, D.[Dominik], Heide, F.[Felix],
ScatterNeRF: Seeing Through Fog with Physically-Based Inverse Neural Rendering,
ICCV23(17911-17922)
IEEE DOI Code:
WWW Link. 2401
BibRef

Zhu, Y.[Yusen], Zhou, G.[Gang], Ren, J.X.[Jing-Xu], Tian, J.[Jiakun], Jia, Z.H.[Zhen-Hong],
Multi-Task Model Based on Vision Task Level for Saliency Object Detection in Foggy Conditions,
ICIP23(3055-3059)
IEEE DOI 2312
BibRef

Zhou, H.Y.[Han-Yu], Chang, Y.[Yi], Yan, W.D.[Wen-Ding], Yan, L.X.[Lu-Xin],
Unsupervised Cumulative Domain Adaptation for Foggy Scene Optical Flow,
CVPR23(9569-9578)
IEEE DOI 2309
BibRef

Jin, Y.Y.[Ye-Ying], Yan, W.D.[Wen-Ding], Yang, W.H.[Wen-Han], Tan, R.T.[Robby T.],
Structure Representation Network and Uncertainty Feedback Learning for Dense Non-uniform Fog Removal,
ACCV22(III:155-172).
Springer DOI 2307
BibRef

Liang, Y.L.[Yan-Lin], Xiong, J.S.[Jian-She], Yang, P.F.[Ping-Fang],
Improved Algorithm for Defogging of Sky Images Based on Dark Channel Prior,
ICIVC22(502-506)
IEEE DOI 2301
Image segmentation, Maximum likelihood detection, Estimation error, Image color analysis, Clustering algorithms, dark channel prior BibRef

Chen, C.[Cheng], Liu, W.[Wei], Lu, T.[Tao],
Single Image Defogging via Recurrent Bilateral Learning,
ICRVC22(193-199)
IEEE DOI 2301
Image resolution, Feature extraction, Image restoration, Convolutional neural networks, Image reconstruction, scene depth BibRef

Graffieti, G.[Gabriele], Maltoni, D.[Davide],
Towards Artifacts-Free Image Defogging,
ICPR21(5060-5067)
IEEE DOI 2105
Measurement, Image edge detection, Manuals, Detectors, Inspection, Data models, Pattern recognition BibRef

Li, Z.[Zhan], Zheng, X.P.[Xiao-Peng], Bhanu, B.[Bir], Long, S.[Shun], Zhang, Q.F.[Qing-Feng], Huang, Z.H.[Zheng-Hao],
Fast Region-Adaptive Defogging and Enhancement for Outdoor Images Containing Sky,
ICPR21(8267-8274)
IEEE DOI 2105
Performance evaluation, Image segmentation, Image color analysis, Imaging, Distortion, Pattern recognition, Image restoration, multi-scale Retinex BibRef

Malav, R.[Ramavtar], Kim, A.[Ayoung], Sahoo, S.R.[Soumya Ranjan], Pandey, G.[Gaurav],
DHSGAN: An End to End Dehazing Network for Fog and Smoke,
ACCV18(V:593-608).
Springer DOI 1906
BibRef

Fan, T.H.[Tang-Huai], Li, C.L.[Chang-Li], Ma, X.[Xiao], Chen, Z.[Zhe], Zhang, X.[Xuan], Chen, L.[Lin],
An improved single image defogging method based on Retinex,
ICIVC17(410-413)
IEEE DOI 1708
image defog, image enhancement, image fusion, retinex, algorithm BibRef

Li, C.L.[Chang-Li], Fan, T.H.[Tang-Huai], Ma, X.[Xiao], Zhang, Z.[Zhen], Wu, H.X.[Hong-Xin], Chen, L.[Lin],
An improved image defogging method based on dark channel prior,
ICIVC17(414-417)
IEEE DOI 1708
Atmosphere, Channel estimation, Estimation, Image color analysis, Image restoration, Optimization, Real-time systems, dark channel prior, image defogging, image enhancement, image, restoration BibRef

Li, Z.[Zhuwen], Tan, P.[Ping], Tan, R.T.[Robby T.], Zou, D.P.[Dan-Ping], Zhou, S.Z.Y.[Steven Zhi-Ying], Cheong, L.F.[Loong-Fah],
Simultaneous video defogging and stereo reconstruction,
CVPR15(4988-4997)
IEEE DOI 1510
BibRef

Minami, Y., Enomoto, K., Migita, M., Toda, M.,
Spatially adaptive image defogging using color characteristics,
FCV15(1-5)
IEEE DOI 1506
aquaculture BibRef

Lee, Y.[Yeejin], Gibson, K.B.[Kristofor B.], Lee, Z.[Zucheul], Nguyen, T.Q.[Truong Q.],
Stereo image defogging,
ICIP14(5427-5431)
IEEE DOI 1502
Atmospheric modeling BibRef

Yuk, J.S.C.[Jacky Shun-Cho], Wong, K.Y.K.[Kwan-Yee Kenneth],
Adaptive Background Defogging with Foreground Decremental Preconditioned Conjugate Gradient,
ACCV12(IV:602-614).
Springer DOI 1304
BibRef

Liu, H.J.[Hong-Jun], Zhou, Y.[Yan], Wang, X.W.[Xin-Wei],
Study of Defog Technology Based on Scattering Model in Assistant Driving System,
CISP09(1-4).
IEEE DOI 0910
BibRef

Xu, Z.Y.[Zhi-Yuan], Liu, X.M.[Xiao-Ming], Ji, N.[Na],
Fog Removal from Color Images using Contrast Limited Adaptive Histogram Equalization,
CISP09(1-5).
IEEE DOI 0910
BibRef

Chapter on Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar continues in
General Weather Enhancement, Restoration .


Last update:Mar 25, 2024 at 16:07:51