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Atmospheric modeling
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JVCIR(25), No. 2, 2014, pp. 445-453.
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1402
Dehaze
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Makarau, A.,
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1407
geophysical image processing
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SPLetters(25), No. 2, February 2018, pp. 219-223.
IEEE DOI
1802
image colour analysis, image denoising, angular components,
angular-based preprocessing, color centers, color decomposition,
nonlocal methods
BibRef
Wang, L.Q.[Li-Qian],
Xiao, L.[Liang],
Wei, Z.H.[Zhi-Hui],
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IET-CV(9), No. 6, 2015, pp. 903-913.
DOI Link
1512
adaptive filters
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Jung, S.W.[Seung-Won],
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JIVP(2016), No. 1, 2016, pp. 4.
DOI Link
1601
BibRef
Fan, X.[Xin],
Wang, Y.[Yi],
Gao, R.J.[Ren-Jie],
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1602
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Gao, R.J.[Ren-Jie],
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Luo, Z.X.[Zhong-Xuan],
Haze filtering with aerial perspective,
ICIP12(989-992).
IEEE DOI
1302
BibRef
Baig, N.,
Riaz, M.M.,
Ghafoor, A.,
Siddiqui, A.M.,
Image Dehazing Using Quadtree Decomposition and Entropy-Based
Contextual Regularization,
SPLetters(23), No. 6, June 2016, pp. 853-857.
IEEE DOI
1606
Computational complexity
BibRef
Liu, C.X.[Chun-Xiao],
Zhao, J.[Jinwei],
Shen, Y.[Yiyun],
Zhou, Y.G.[Yang-Gang],
Wang, X.[Xun],
Ouyang, Y.[Yi],
Texture filtering based physically plausible image dehazing,
VC(32), No. 6-8, June 2016, pp. 911-920.
Springer DOI
1608
BibRef
Wallace, B.[Bruce],
Degraded visual environments present challenges for DARPA,
SPIE(Newsroom), September 6, 2016
DOI Link
1610
Seeing through smoke, dust, clouds, or other obscurants is the focus
of the agency's strategic efforts in imaging.
BibRef
He, L.,
Zhao, J.,
Zheng, N.,
Bi, D.,
Haze Removal Using the Difference- Structure-Preservation Prior,
IP(26), No. 3, March 2017, pp. 1063-1075.
IEEE DOI
1703
image denoising
BibRef
Wang, W.,
Yuan, X.,
Wu, X.,
Liu, Y.,
Fast Image Dehazing Method Based on Linear Transformation,
MultMed(19), No. 6, June 2017, pp. 1142-1155.
IEEE DOI
1705
Atmospheric modeling, Computational modeling, Filtering,
Image color analysis, Image restoration, Meteorology, Scattering,
Dehazing, image restoration, linear transformation, transmission, map
BibRef
Jang, D.W.[Dong-Won],
Park, R.H.[Rae-Hong],
Colour image dehazing using near-infrared fusion,
IET-IPR(11), No. 8, August 2017, pp. 587-594.
DOI Link
1708
BibRef
Jang, D.W.[Dong-Won],
Kim, H.S.[Hyo-Song],
Jung, C.D.[Chang-Dae],
Park, R.H.[Rae-Hong],
Color fringe correction based on image fusion,
ICIP14(1817-1821)
IEEE DOI
1502
Adaptive optics
BibRef
Yang, J.C.[Jia-Chen],
Jiang, B.[Bin],
Lv, Z.H.[Zhi-Han],
Jiang, N.[Na],
A real-time image dehazing method considering dark channel and
statistics features,
RealTimeIP(13), No. 3, September 2017, pp. 479-490.
WWW Link.
1710
BibRef
Sun, L.X.[Li-Xin],
Latifovic, R.[Rasim],
Pouliot, D.[Darren],
Haze Removal Based on a Fully Automated and Improved Haze Optimized
Transformation for Landsat Imagery over Land,
RS(9), No. 10, 2017, pp. xx-yy.
DOI Link
1711
BibRef
Nair, D.[Deepa],
Sankaran, P.[Praveen],
Color image dehazing using surround filter and dark channel prior,
JVCIR(50), No. 1, 2018, pp. 9-15.
Elsevier DOI
1712
Atmospheric light
BibRef
Xiao, J.S.[Jin-Sheng],
Zhu, L.[Li],
Zhang, Y.Q.[Yong-Qin],
Liu, E.[Enyu],
Lei, J.F.[Jun-Feng],
Scene-aware image dehazing based on sky-segmented dark channel prior,
IET-IPR(11), No. 12, Decmeber 2017, pp. 1163-1171.
DOI Link
1712
BibRef
Li, Y.[Yu],
You, S.D.[Shao-Di],
Brown, M.S.[Michael S.],
Tan, R.T.[Robby T.],
Haze visibility enhancement: A Survey and quantitative benchmarking,
CVIU(165), No. 1, 2017, pp. 1-16.
Elsevier DOI
1712
BibRef
Earlier: A1, A4, A3, Only:
Nighttime Haze Removal with Glow and Multiple Light Colors,
ICCV15(226-234)
IEEE DOI
1602
Scattering media.
Atmospheric modeling
BibRef
Jiang, Y.T.[Yu-Tong],
Sun, C.M.[Chang-Ming],
Zhao, Y.[Yu],
Yang, L.[Li],
Image dehazing using adaptive bi-channel priors on superpixels,
CVIU(165), No. 1, 2017, pp. 17-32.
Elsevier DOI
1712
Image restoration
BibRef
Zhu, M.Z.[Ming-Zhu],
He, B.W.[Bing-Wei],
Zhang, L.W.[Li-Wei],
Atmospheric light estimation in hazy images based on color-plane
model,
CVIU(165), No. 1, 2017, pp. 33-42.
Elsevier DOI
1712
Dehaze
BibRef
Fan, X.,
Wang, Y.,
Tang, X.X.[Xian-Xuan],
Gao, R.,
Luo, Z.X.[Zhong-Xuan],
Two-Layer Gaussian Process Regression With Example Selection for
Image Dehazing,
CirSysVideo(27), No. 12, December 2017, pp. 2505-2517.
IEEE DOI
1712
Computational modeling, Estimation, Gaussian processes,
Ground penetrating radar, Image resolution, Image restoration,
image dehazing
BibRef
Fan, X.[Xin],
Tang, X.X.[Xian-Xuan],
Hou, M.J.[Min-Jun],
Luo, Z.X.[Zhong-Xuan],
Fast example searching for input-adaptive data-driven dehazing with
Gaussian process regression,
VC(35), No. 4, April 2019, pp. 565-577.
WWW Link.
1906
BibRef
Zhao, X.T.[Xin-Tao],
Ding, W.R.[Wen-Rui],
Liu, C.H.[Chun-Hui],
Li, H.G.[Hong-Guang],
Haze removal for unmanned aerial vehicle aerial video based on
spatial-temporal coherence optimisation,
IET-IPR(12), No. 1, January 2018, pp. 88-97.
DOI Link
1712
BibRef
Singh, D.[Dilbag],
Kumar, V.[Vijay],
Dehazing of remote sensing images using fourth-order partial
differential equations based trilateral filter,
IET-CV(12), No. 2, March 2018, pp. 208-219.
DOI Link
1804
BibRef
Qin, K.[Kai],
Wang, L.[Luyao],
Xu, J.[Jian],
Letu, H.[Husi],
Zhang, K.[Kefei],
Li, D.[Ding],
Zou, J.H.[Jia-Heng],
Fan, W.Z.[Wen-Zhi],
Haze Optical Properties from Long-Term Ground-Based Remote Sensing
over Beijing and Xuzhou, China,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link
1805
BibRef
Yuan, F.,
Huang, H.,
Image Haze Removal via Reference Retrieval and Scene Prior,
IP(27), No. 9, September 2018, pp. 4395-4409.
IEEE DOI
1807
image denoising, image enhancement, image restoration,
image retrieval, external information,
scene transmission
BibRef
Zhang, Y.,
Wang, X.,
Bi, X.,
Tao, D.,
A Light Dual-Task Neural Network for Haze Removal,
SPLetters(25), No. 8, August 2018, pp. 1231-1235.
IEEE DOI
1808
feature extraction, image enhancement, image restoration,
neural nets, light dual-task Neural Network, haze removal,
image restoration
BibRef
Salazar-Colores, S.[Sebastián],
Ramos-Arreguín, J.M.[Juan-Manuel],
Ortiz Echeverri, C.J.[César Javier],
Cabal-Yepez, E.[Eduardo],
Pedraza-Ortega, J.C.[Jesus-Carlos],
Rodriguez-Resendiz, J.[Juvenal],
Image dehazing using morphological opening, dilation and Gaussian
filtering,
SIViP(12), No. 7, October 2018, pp. 1329-1335.
Springer DOI
1809
BibRef
Son, C.,
Zhang, X.,
Near-Infrared Fusion via Color Regularization for Haze and Color
Distortion Removals,
CirSysVideo(28), No. 11, November 2018, pp. 3111-3126.
IEEE DOI
1811
Image color analysis, Color, Distortion, Degradation,
Atmospheric modeling, Imaging, Coloring,
near-infrared imaging
BibRef
Chen, Y.[Yang],
Khosla, D.[Deepak],
Fast Image Dehazing Methods for Real-Time Video Processing,
ISVC18(619-628).
Springer DOI
1811
BibRef
Singh, D.[Dilbag],
Kumar, V.[Vijay],
Image dehazing using Moore neighborhood-based gradient profile prior,
SP:IC(70), 2019, pp. 131-144.
Elsevier DOI
1812
Hazy images, Moore neighborhood-based gradient profile prior,
Local activity-tuned anisotropic diffusion, Transmission map
BibRef
Ren, W.,
Zhang, J.,
Xu, X.,
Ma, L.,
Cao, X.,
Meng, G.,
Liu, W.,
Deep Video Dehazing With Semantic Segmentation,
IP(28), No. 4, April 2019, pp. 1895-1908.
IEEE DOI
1901
feature extraction, feedforward neural nets, image denoising,
image enhancement, image restoration, image segmentation,
convolutional neural network
BibRef
Li, C.[Ce],
Zhao, X.Y.[Xin-Yu],
Zhang, Z.X.[Zhao-Xiang],
Du, S.Y.[Shao-Yi],
Generative adversarial dehaze mapping nets,
PRL(119), 2019, pp. 238-244.
Elsevier DOI
1902
GADMN, Haze-relevant features, Multiple-light scattering model, LMHPM
BibRef
Nnolim, U.A.[Uche A.],
Formulation of Fractional Derivative-Based De-Hazing Algorithm and
Implementation on Mobile-Embedded Devices,
IJIG(19), No. 1 2018, pp. 1950003.
DOI Link
1902
BibRef
Salazar-Colores, S.,
Cabal-Yepez, E.,
Ramos-Arreguin, J.M.,
Botella, G.,
Ledesma-Carrillo, L.M.,
Ledesma, S.,
A Fast Image Dehazing Algorithm Using Morphological Reconstruction,
IP(28), No. 5, May 2019, pp. 2357-2366.
IEEE DOI
1903
image restoration, dehazing algorithms, transmission maps,
depth maps, image restoration, restoration algorithm,
dark channel prior
BibRef
Liu, P.,
Horng, S.,
Lin, J.,
Li, T.,
Contrast in Haze Removal:
Configurable Contrast Enhancement Model Based on Dark Channel Prior,
IP(28), No. 5, May 2019, pp. 2212-2227.
IEEE DOI
1903
image colour analysis, image enhancement, image restoration,
dark channel prior, color constancy method, contrast values,
color de-correlating
BibRef
Shen, L.,
Zhao, Y.,
Peng, Q.,
Chan, J.C.,
Kong, S.G.,
An Iterative Image Dehazing Method With Polarization,
MultMed(21), No. 5, May 2019, pp. 1093-1107.
IEEE DOI
1905
image denoising, iterative methods, polarizing images,
denoising scheme, iterative image dehazing method,
weighted regularization
BibRef
Yang, C.W.[Chen-Wei],
Feng, H.J.[Hua-Jun],
Xu, Z.H.[Zhi-Hai],
Li, Q.[Qi],
Chen, Y.T.[Yue-Ting],
Correction of overexposure utilizing haze removal model and image
fusion technique,
VC(35), No. 5, May 2019, pp. 695-705.
WWW Link.
1906
BibRef
Zhu, M.,
He, B.,
Liu, J.,
Zhang, L.,
Dark Channel: The Devil is in the Details,
SPLetters(26), No. 7, July 2019, pp. 981-985.
IEEE DOI
1906
image colour analysis, image restoration, dark channel,
haze removal, dark pixel, transmission estimation method,
dark pixel
BibRef
Lee, Y.,
Wu, B.,
Algorithm and Architecture Design of a Hardware-Efficient Image
Dehazing Engine,
CirSysVideo(29), No. 7, July 2019, pp. 2146-2161.
IEEE DOI
1907
Hardware, Atmospheric modeling, Estimation,
Image resolution, Throughput, Scattering, Airlight, area efficiency,
transmission rate
BibRef
Min, X.,
Zhai, G.,
Gu, K.,
Yang, X.,
Guan, X.,
Objective Quality Evaluation of Dehazed Images,
ITS(20), No. 8, August 2019, pp. 2879-2892.
IEEE DOI
1908
Feature extraction, Meteorology, Indexes, Image color analysis,
Intelligent transportation systems, Intelligent systems,
dehazing algorithm evaluation
BibRef
Ju, M.,
Ding, C.,
Zhang, D.,
Guo, Y.J.,
BDPK: Bayesian Dehazing Using Prior Knowledge,
CirSysVideo(29), No. 8, August 2019, pp. 2349-2362.
IEEE DOI
1908
Atmospheric modeling, Scattering, Image color analysis,
Bayes methods, Computational modeling, Image restoration,
scattering distribution
BibRef
El-Hashash, M.M.[Mostafa M.],
Aly, H.A.[Hussein A.],
High-speed video haze removal algorithm for embedded systems,
RealTimeIP(16), No. 4, August 2019, pp. 1117-1128.
WWW Link.
1908
BibRef
And:
Erratum:
RealTimeIP(16), No. 5, October 2019, pp. 1887.
WWW Link.
1911
BibRef
Min, X.,
Zhai, G.,
Gu, K.,
Zhu, Y.,
Zhou, J.,
Guo, G.,
Yang, X.,
Guan, X.,
Zhang, W.,
Quality Evaluation of Image Dehazing Methods Using Synthetic Hazy
Images,
MultMed(21), No. 9, September 2019, pp. 2319-2333.
IEEE DOI
1909
Atmospheric modeling, Image color analysis,
Atmospheric measurements, Databases, Scattering,
regular/aerial image
BibRef
Ancuti, C.O.,
Ancuti, C.,
de Vleeschouwer, C.,
Sbetr, M.,
Color Channel Transfer for Image Dehazing,
SPLetters(26), No. 9, September 2019, pp. 1413-1417.
IEEE DOI
1909
Image color analysis, Attenuation, Lighting, Scattering,
Optical attenuators, Optical imaging, Atmospheric modeling,
image enhancement
BibRef
Kumar, H.[Himanshu],
Gupta, S.[Sumana],
Venkatesh, K.S.[K. Subramanian],
Realtime dehazing using colour uniformity principle,
IET-IPR(13), No. 11, 19 September 2019, pp. 1931-1939.
DOI Link
1909
BibRef
Guo, Q.,
Hu, H.,
Li, B.,
Haze and Thin Cloud Removal Using Elliptical Boundary Prior for
Remote Sensing Image,
GeoRS(57), No. 11, November 2019, pp. 9124-9137.
IEEE DOI
1911
Remote sensing, Sensors, Correlation, Cloud computing, Estimation,
Clouds, Earth, Elliptical boundary, haze thickness prior, visible remote sensing image dehazing
BibRef
Pang, Y.,
Xie, J.,
Li, X.,
Visual Haze Removal by a Unified Generative Adversarial Network,
CirSysVideo(29), No. 11, November 2019, pp. 3211-3221.
IEEE DOI
1911
Atmospheric modeling, Generators,
Generative adversarial networks, Feature extraction,
convolutional neural network
BibRef
Gu, Y.[Yanan],
Yang, X.P.[Xiao-Ping],
Gao, Y.M.[Yi-Ming],
A Novel Total Generalized Variation Model for Image Dehazing,
JMIV(61), No. 9, November 2019, pp. 1329-1341.
WWW Link.
1911
BibRef
Diaz-Ramirez, V.H.[Victor H.],
Hernández-Beltrán, J.E.[José Enrique],
Juarez-Salazar, R.[Rigoberto],
Real-time haze removal in monocular images using locally adaptive
processing,
RealTimeIP(16), No. 6, December 2019, pp. 1959-1973.
Springer DOI
1912
BibRef
Wu, Q.,
Ren, W.,
Cao, X.,
Learning Interleaved Cascade of Shrinkage Fields for Joint Image
Dehazing and Denoising,
IP(29), No. 1, 2020, pp. 1788-1801.
IEEE DOI
1912
Noise reduction, Noise measurement, Atmospheric modeling,
Estimation, Task analysis, Standards, Convolution, Image dehazing,
interleaved cascade of shrinkage fields
BibRef
Wang, W.,
Li, Z.,
Wu, S.,
Zeng, L.,
Hazy Image Decolorization With Color Contrast Restoration,
IP(29), No. 1, 2020, pp. 1776-1787.
IEEE DOI
1912
Image color analysis, Gray-scale, Image restoration,
Nonlinear distortion, Colored noise, Optimization, Decolorization,
spatially varying linear mapping
BibRef
Qiu, B.[Bin],
Liang, X.[Xiwen],
Su, Z.[Zhuo],
Wang, R.[Ruomei],
Zhou, F.[Fan],
Learning mean progressive scattering using binomial truncated loss for
image dehazing,
IET-IPR(13), No. 14, 12 December 2019, pp. 2929-2939.
DOI Link
1912
BibRef
Li, M.[Ming],
Chen, X.D.[Xu-Dong],
Peng, C.L.[Cheng-Lei],
Du, S.[Sidan],
Li, Y.[Yang],
Modeling the occlusion problem in thermal imaging to allow seeing
through mist and foliage,
JOSA-A(36), No. 2, February 2019, pp. A67-A76.
DOI Link
1912
Image processing, Infrared radiation, Plenoptic imaging,
Synthetic aperture radar, Thermal imaging, Visible light
BibRef
Mandal, S.,
Rajagopalan, A.N.,
Local Proximity for Enhanced Visibility in Haze,
IP(29), 2020, pp. 2478-2491.
IEEE DOI
2001
Dehazing, contrast enhancement, patch similarity, underwater
BibRef
Ancuti, C.O.,
Ancuti, C.,
de Vleeschouwer, C.,
Sbert, M.,
Color Channel Compensation (3C):
A Fundamental Pre-Processing Step for Image Enhancement,
IP(29), 2020, pp. 2653-2665.
IEEE DOI
2001
Image enhancement, dehazing, color-constancy
BibRef
Li, L.,
Dong, Y.,
Ren, W.,
Pan, J.,
Gao, C.,
Sang, N.,
Yang, M.,
Semi-Supervised Image Dehazing,
IP(29), 2020, pp. 2766-2779.
IEEE DOI
2001
Image dehazing, deep learning, semi-supervised learning
BibRef
Wierzbicki, D.[Damian],
Kedzierski, M.[Michal],
Sekrecka, A.[Aleksandra],
A Method for Dehazing Images Obtained from Low Altitudes during
High-Pressure Fronts,
RS(12), No. 1, 2019, pp. xx-yy.
DOI Link
2001
BibRef
Ju, M.,
Ding, C.,
Guo, Y.J.,
Zhang, D.,
IDGCP: Image Dehazing Based on Gamma Correction Prior,
IP(29), 2020, pp. 3104-3118.
IEEE DOI
2002
Atmospheric scattering theory, gamma correction prior (GCP),
global-wise strategy, haze removal, processing time, vision indicator
BibRef
Yin, S.[Shibai],
Wang, Y.[Yibin],
Yang, Y.H.[Yee-Hong],
A novel image-dehazing network with a parallel attention block,
PR(102), 2020, pp. 107255.
Elsevier DOI
2003
Image dehazing, Spatial attention mechanism,
Channel-wise attention mechanism, Encoder-decoder, CNN
BibRef
Ali, H.[Haider],
Sher, A.[Awal],
Saeed, M.[Maryam],
Rada, L.[Lavdie],
Active contour image segmentation model with de-hazing constraints,
IET-IPR(14), No. 5, 17 April 2020, pp. 921-928.
DOI Link
2004
BibRef
Fan, Y.L.[Yong-Lei],
Rui, X.P.[Xiao-Ping],
Poslad, S.[Stefan],
Zhang, G.Y.[Guang-Yuan],
Yu, T.[Tian],
Xu, X.J.[Xi-Jie],
Song, X.F.[Xian-Feng],
A better way to monitor haze through image based upon the adjusted
LeNet-5 CNN model,
SIViP(14), No. 3, April 2020, pp. 455-463.
Springer DOI
2004
BibRef
Song, T.[Taeyong],
Kim, Y.J.[Young-Jung],
Oh, C.J.[Chang-Jae],
Jang, H.S.[Hyun-Sung],
Ha, N.[Namkoo],
Sohn, K.H.[Kwang-Hoon],
Simultaneous Deep Stereo Matching and Dehazing with Feature Attention,
IJCV(128), No. 4, April 2020, pp. 799-817.
Springer DOI
2004
See also Memory-Guided Image De-Raining Using Time-Lapse Data.
BibRef
Peng, Y.,
Lu, Z.,
Cheng, F.,
Zheng, Y.,
Huang, S.,
Image Haze Removal Using Airlight White Correction, Local Light
Filter, and Aerial Perspective Prior,
CirSysVideo(30), No. 5, May 2020, pp. 1385-1395.
IEEE DOI
2005
Image color analysis, Optical filters, Optical distortion,
Optical imaging, Atmospheric modeling, Estimation, Adaptive optics,
aerial perspective prior
BibRef
Yuan, F.N.[Fei-Niu],
Zhou, Y.[Yu],
Xia, X.[Xue],
Shi, J.T.[Jin-Ting],
Fang, Y.M.[Yu-Ming],
Qian, X.M.[Xue-Ming],
Image dehazing based on a transmission fusion strategy by automatic
image matting,
CVIU(194), 2020, pp. 102933.
Elsevier DOI
2005
Transmission fusion, Image matting, Image dehazing,
Dark channel prior, Veil correction
BibRef
Nnolim, U.A.,
Probabilistic, Multi-Scale Fractional Tonal Correction Bilateral
Filter-Based Hazy Image Enhancement,
IJIG(20), No. 2, April 2020, pp. 2050010.
DOI Link
2005
BibRef
Ancuti, C.,
Ancuti, C.O.,
de Vleeschouwer, C.,
Bovik, A.C.,
Day and Night-Time Dehazing by Local Airlight Estimation,
IP(29), 2020, pp. 6264-6275.
IEEE DOI
2005
Local airlight, haze, dehazing, night-time, fusion
BibRef
Vazquez-Corral, J.[Javier],
Galdran, A.[Adrian],
Cyriac, P.[Praveen],
Bertalmío, M.[Marcelo],
A fast image dehazing method that does not introduce color artifacts,
RealTimeIP(17), No. 3, June 2020, pp. 607-622.
Springer DOI
2006
BibRef
Zhang, S.D.[Sheng-Dong],
He, F.Z.[Fa-Zhi],
Ren, W.Q.[Wen-Qi],
Photo-realistic dehazing via contextual generative adversarial networks,
MVA(31), No. 5, July 2020, pp. Article33.
WWW Link.
2006
BibRef
Zhang, H.,
Sindagi, V.,
Patel, V.M.,
Joint Transmission Map Estimation and Dehazing Using Deep Networks,
CirSysVideo(30), No. 7, July 2020, pp. 1975-1986.
IEEE DOI
2007
Propagation losses, Atmospheric modeling, Estimation,
Feature extraction, Task analysis,
low-level vision
BibRef
Li, R.,
Pan, J.,
He, M.,
Li, Z.,
Tang, J.,
Task-Oriented Network for Image Dehazing,
IP(29), 2020, pp. 6523-6534.
IEEE DOI
2007
Task analysis, Image color analysis, Atmospheric modeling,
Image restoration, Distortion, Convolutional neural networks,
image restoration
BibRef
Zhao, S.,
Zhang, L.,
Huang, S.,
Shen, Y.,
Zhao, S.,
Dehazing Evaluation: Real-World Benchmark Datasets, Criteria, and
Baselines,
IP(29), 2020, pp. 6947-6962.
IEEE DOI
2007
Measurement, Benchmark testing, Indexes, Image restoration,
Distortion, Image quality, Reliability, Benchmark dataset,
FR-IQA
BibRef
Wang, R.,
Ji, T.,
Wang, G.,
Haze Removal by Modeling the Scattering Properties of the Medium,
SPLetters(27), 2020, pp. 1155-1159.
IEEE DOI
2007
Backscatter, haze removal, image recovery
BibRef
Qi, B.J.[Bao-Jun],
Yang, C.F.[Chun-Fang],
Tan, L.[Lei],
Luo, X.Y.[Xiang-Yang],
Liu, F.L.[Fen-Lin],
A novel haze image steganography method via cover-source switching,
JVCIR(70), 2020, pp. 102814.
Elsevier DOI
2007
Steganography, Haze image, Natural steganography, UNIWARD, Steganalysis
BibRef
Dong, H.[Hang],
Pan, J.S.[Jin-Shan],
Xiang, L.[Lei],
Hu, Z.[Zhe],
Zhang, X.Y.[Xin-Yi],
Wang, F.[Fei],
Yang, M.H.[Ming-Hsuan],
Multi-Scale Boosted Dehazing Network with Dense Feature Fusion,
CVPR20(2154-2164)
IEEE DOI
2008
Boosting, Image restoration, Decoding, Task analysis,
Feature extraction, Atmospheric modeling, Fuses
BibRef
Shao, Y.,
Li, L.,
Ren, W.,
Gao, C.,
Sang, N.,
Domain Adaptation for Image Dehazing,
CVPR20(2805-2814)
IEEE DOI
2008
Adaptation models, Training, Atmospheric modeling, Data models,
Image color analysis, Bridges
BibRef
Hong, M.,
Xie, Y.,
Li, C.,
Qu, Y.,
Distilling Image Dehazing With Heterogeneous Task Imitation,
CVPR20(3459-3468)
IEEE DOI
2008
Pattern recognition
BibRef
Dudhane, A.,
Biradar, K.M.,
Patil, P.W.,
Hambarde, P.,
Murala, S.,
Varicolored Image De-Hazing,
CVPR20(4563-4572)
IEEE DOI
2008
Image color analysis, Atmospheric modeling, Image restoration,
Meteorology, Scattering, Feature extraction, Generators
BibRef
Pang, Y.,
Nie, J.,
Xie, J.,
Han, J.,
Li, X.,
BidNet: Binocular Image Dehazing Without Explicit Disparity
Estimation,
CVPR20(5930-5939)
IEEE DOI
2008
Estimation, Atmospheric modeling, Correlation, Machine learning,
Task analysis, Scattering
BibRef
Mehta, A.,
Sinha, H.,
Narang, P.,
Mandal, M.,
HIDeGan: A Hyperspectral-guided Image Dehazing GAN,
VAS20(846-856)
IEEE DOI
2008
Image reconstruction, Hyperspectral imaging,
Atmospheric modeling, Image color analysis, Skeleton, Generators
BibRef
Liu, J.,
Wu, H.,
Xie, Y.,
Qu, Y.,
Ma, L.,
Trident Dehazing Network,
NTIRE20(1732-1741)
IEEE DOI
2008
Image reconstruction, Frequency-domain analysis,
Feature extraction, Training, Atmospheric modeling, Convolution
BibRef
Yu, M.,
Cherukuri, V.,
Guo, T.,
Monga, V.,
Ensemble Dehazing Networks for Non-homogeneous Haze,
NTIRE20(1832-1841)
IEEE DOI
2008
Decoding, Task analysis, Inverse problems, Machine learning,
Training, Measurement
BibRef
Metwaly, K.,
Li, X.,
Guo, T.,
Monga, V.,
NonLocal Channel Attention for NonHomogeneous Image Dehazing,
NTIRE20(1842-1851)
IEEE DOI
2008
Decoding, Feature extraction, Estimation, Mathematical model,
Machine learning, Measurement
BibRef
Wu, H.,
Liu, J.,
Xie, Y.,
Qu, Y.,
Ma, L.,
Knowledge Transfer Dehazing Network for NonHomogeneous Dehazing,
NTIRE20(1975-1983)
IEEE DOI
2008
Task analysis, Training, Knowledge engineering, Convolution,
Knowledge transfer, Image color analysis, Atmospheric modeling
BibRef
Das, S.D.,
Dutta, S.,
Fast Deep Multi-patch Hierarchical Network for Nonhomogeneous Image
Dehazing,
NTIRE20(1994-2001)
IEEE DOI
2008
Decoding, Atmospheric modeling, Machine learning, Scattering,
Image reconstruction, Runtime, Feature extraction
BibRef
Zhang, S.,
Wu, Y.,
Zhao, Y.,
Cheng, Z.,
Ren, W.,
Color-Constrained Dehazing Model,
UG20(3799-3807)
IEEE DOI
2008
Image color analysis, Atmospheric modeling, Colored noise,
Scattering, Distortion, Smoothing methods, Attenuation
BibRef
Yan, Y.,
Zhang, S.,
Ju, M.,
Ren, W.,
Wang, R.,
Guo, Y.,
A Point Light Source Interference Removal Method for Image Dehazing,
UG20(3817-3825)
IEEE DOI
2008
Light sources, Atmospheric modeling, Image color analysis,
Estimation, Gaussian distribution, Scattering, Attenuation
BibRef
Zhang, X.Q.[Xiao-Qin],
Wang, T.[Tao],
Wang, J.X.[Jin-Xin],
Tang, G.Y.[Gui-Ying],
Zhao, L.[Li],
Pyramid Channel-based Feature Attention Network for image dehazing,
CVIU(197-198), 2020, pp. 103003.
Elsevier DOI
2008
Image dehazing, Deep neural network, Channel attention
BibRef
Zhang, S.D.[Sheng-Dong],
He, F.Z.[Fa-Zhi],
DRCDN: learning deep residual convolutional dehazing networks,
VC(36), No. 9, September 2020, pp. 1797-1808.
WWW Link.
2008
BibRef
Yang, Y.,
Wang, Z.,
Haze Removal: Push DCP at the Edge,
SPLetters(27), 2020, pp. 1405-1409.
IEEE DOI
2008
Information filters, Filtering theory, Image edge detection,
Attenuation, Image coding, Distortion, Image dehazing, filter
BibRef
Shen, H.,
Zhang, C.,
Li, H.,
Yuan, Q.,
Zhang, L.,
A Spatial-Spectral Adaptive Haze Removal Method for Visible Remote
Sensing Images,
GeoRS(58), No. 9, September 2020, pp. 6168-6180.
IEEE DOI
2008
Atmospheric modeling, Remote sensing, Scattering, Distortion,
Indexes, Image color analysis, Bright pixel index (BPI),
spatial-spectral adaptive
BibRef
Harish Babu, G.,
Venkatram, N.,
A survey on analysis and implementation of state-of-the-art haze
removal techniques,
JVCIR(72), 2020, pp. 102912.
Elsevier DOI
1806
Survey, Haze Removal. Opalescent, Image dehazing, Image restoration,
Computational time, Machine learning, Deep learning, Hardware implementation
BibRef
Yin, J.L.,
Huang, Y.C.,
Chen, B.H.,
Ye, S.Z.,
Color Transferred Convolutional Neural Networks for Image Dehazing,
CirSysVideo(30), No. 11, November 2020, pp. 3957-3967.
IEEE DOI
2011
Atmospheric modeling, Image color analysis,
Integrated circuit modeling, Estimation, Standards,
deep learning
BibRef
Yin, S.B.[Shi-Bai],
Xin, J.[Jin],
Wang, Y.B.[Yi-Bin],
Basu, A.[Anup],
Image dehazing with uneven illumination prior by dense residual channel
attention network,
IET-IPR(14), No. 13, November 2020, pp. 3260-3272.
DOI Link
2012
BibRef
Tang, Q.F.[Qun-Fang],
Yang, J.[Jie],
He, X.J.[Xiang-Jian],
Jia, W.J.[Wen-Jing],
Zhang, Q.N.[Qing-Nian],
Liu, H.B.[Hai-Bo],
Nighttime image dehazing based on Retinex and dark channel prior
using Taylor series expansion,
CVIU(202), 2021, pp. 103086.
Elsevier DOI
2012
Nighttime image dehazing, Retinex theory,
Taylor series expansion, Image fusion, Color transfer
BibRef
Li, P.Y.[Peng-Yue],
Tian, J.D.[Jian-Dong],
Tang, Y.D.[Yan-Dong],
Wang, G.L.[Guo-Lin],
Wu, C.G.[Chen-Gdong],
Deep Retinex Network for Single Image Dehazing,
IP(30), 2021, pp. 1100-1115.
IEEE DOI
2012
Lighting, Atmospheric modeling, Scattering, Image color analysis,
Image restoration, Predictive models, Brightness, Image dehazing,
image restoration
BibRef
Hu, A.[Anna],
Xie, Z.[Zhong],
Xu, Y.Y.[Yong-Yang],
Xie, M.Y.[Ming-Yu],
Wu, L.[Liang],
Qiu, Q.J.[Qin-Jun],
Unsupervised Haze Removal for High-Resolution Optical Remote-Sensing
Images Based on Improved Generative Adversarial Networks,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link
2012
BibRef
Li, Y.,
Liu, Y.,
Yan, Q.,
Zhang, K.,
Deep Dehazing Network With Latent Ensembling Architecture and
Adversarial Learning,
IP(30), 2021, pp. 1354-1368.
IEEE DOI
2012
Atmospheric modeling, Imaging, Training, Task analysis, Cameras,
Neural networks, Estimation, Dehazing, haze removal,
object detection
BibRef
Wu, X.Y.[Xian-Yun],
Wang, K.[Keyan],
Li, Y.[Yunsong],
Liu, K.[Kai],
Huang, B.[Bormin],
Accelerating Haze Removal Algorithm Using CUDA,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link
2101
BibRef
Gautam, S.[Sidharth],
Gandhi, T.K.[Tapan Kumar],
Panigrahi, B.K.,
A Model-based dehazing scheme for unmanned aerial vehicle system
using radiance boundary constraint and graph model,
JVCIR(74), 2021, pp. 102993.
Elsevier DOI
2101
Remote sensing, Satellite imaging,
Unmanned aerial vehicle imaging, Image restoration,
Image dehazing
BibRef
Nair, D.[Deepa],
Sankaran, P.[Praveen],
A modular architecture for high resolution image dehazing,
SP:IC(92), 2021, pp. 116113.
Elsevier DOI
2101
Dehazing, image quality assessment, Laplacian matrix, Poisson solver
BibRef
Ju, M.,
Ding, C.,
Ren, W.,
Yang, Y.,
Zhang, D.,
Guo, Y.J.,
IDE: Image Dehazing and Exposure Using an Enhanced Atmospheric
Scattering Model,
IP(30), 2021, pp. 2180-2192.
IEEE DOI
2102
geophysical image processing, image colour analysis,
image enhancement, image restoration, IDE,
scene exposure
BibRef
Guo, J.,
Yang, J.,
Yue, H.,
Tan, H.,
Hou, C.,
Li, K.,
RSDehazeNet: Dehazing Network With Channel Refinement for
Multispectral Remote Sensing Images,
GeoRS(59), No. 3, March 2021, pp. 2535-2549.
IEEE DOI
2103
Feature extraction, Remote sensing, Correlation,
Image color analysis, Cloud computing, Training, Earth,
wavelength dependence
BibRef
Zhao, C.Y.[Chao-Yue],
Jia, R.S.[Rui-Sheng],
Liu, Q.M.[Qing-Ming],
Sun, H.M.[Hong-Mei],
Sun, H.B.[Hai-Bin],
Image dehazing method via a cycle generative adversarial network,
IET-IPR(14), No. 16, 19 December 2020, pp. 4240-4247.
DOI Link
2103
BibRef
Satrasupalli, S.[Sivaji],
Daniel, E.[Ebenezer],
Guntur, S.R.[Sitaramanjaneya Reddy],
Shehanaz, S.[Shaik],
End to end system for hazy image classification and reconstruction
based on mean channel prior using deep learning network,
IET-IPR(14), No. 17, 24 December 2020, pp. 4736-4743.
DOI Link
2104
BibRef
Liu, R.,
Li, S.,
Liu, J.,
Ma, L.,
Fan, X.,
Luo, Z.,
Learning Hadamard-Product-Propagation for Image Dehazing and Beyond,
CirSysVideo(31), No. 4, April 2021, pp. 1366-1379.
IEEE DOI
2104
Task analysis, Image enhancement, Atmospheric modeling,
Image color analysis, Deep learning, Image restoration, Distortion,
image dehazing
BibRef
Dhara, S.K.[Sobhan Kanti],
Roy, M.[Mayukh],
Sen, D.[Debashis],
Biswas, P.K.[Prabir Kumar],
Color Cast Dependent Image Dehazing via Adaptive Airlight Refinement
and Non-Linear Color Balancing,
CirSysVideo(31), No. 5, 2021, pp. 2076-2081.
IEEE DOI
2105
BibRef
Mehra, A.[Aryan],
Narang, P.[Pratik],
Mandal, M.[Murari],
TheiaNet: Towards fast and inexpensive CNN design choices for image
dehazing,
JVCIR(77), 2021, pp. 103137.
Elsevier DOI
2106
Dehazing, Computation efficiency, Speed and memory tests, Design choices
BibRef
Agrawal, S.C.[Subhash Chand],
Jalal, A.S.[Anand Singh],
A joint cumulative distribution function and gradient fusion based
method for dehazing of long shot hazy images,
JVCIR(77), 2021, pp. 103087.
Elsevier DOI
2106
Image dehazing, Joint cumulative distribution, Nearby haze,
Faraway haze, Image fusion, Gradient domain
BibRef
Kim, G.[Guisik],
Park, S.W.[Sung Woo],
Kwon, J.[Junseok],
Pixel-Wise Wasserstein Autoencoder for Highly Generative Dehazing,
IP(30), 2021, pp. 5452-5462.
IEEE DOI
2106
Tensors, Image enhancement, Lighting, Network architecture,
Estimation, Channel estimation, Transforms, Dehazing,
image enhancement
BibRef
Lee, Y.H.[Yu-Hsuan],
Tang, S.J.[Sheng-Jie],
A Design of Image Dehazing Engine Using DTE and DAE Techniques,
CirSysVideo(31), No. 7, July 2021, pp. 2880-2895.
IEEE DOI
2107
Scattering, Engines, Estimation, Artificial intelligence, Throughput,
Atmospheric modeling, Image resolution, Image dehazing, airlight,
energy efficiency
BibRef
Zhu, Z.Q.[Zhi-Qin],
Luo, Y.Q.[Ya-Qin],
Wei, H.Y.[Hong-Yan],
Li, Y.[Yong],
Qi, G.Q.[Guan-Qiu],
Mazur, N.[Neal],
Li, Y.Y.[Yuan-Yuan],
Li, P.[Penglong],
Atmospheric Light Estimation Based Remote Sensing Image Dehazing,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Kumar, A.[Avishek],
Jha, R.K.[Rajib Kumar],
Nishchal, N.K.[Naveen K.],
An improved Gamma correction model for image dehazing in a
multi-exposure fusion framework,
JVCIR(78), 2021, pp. 103122.
Elsevier DOI
2107
Image dehazing, Gamma correction model, Multi-exposure fusion
BibRef
Yuan, F.N.[Fei-Niu],
Zhou, Y.[Yu],
Xia, X.[Xue],
Qian, X.M.[Xue-Ming],
Huang, J.[Jian],
A confidence prior for image dehazing,
PR(119), 2021, pp. 108076.
Elsevier DOI
2108
Regression, Classification, Image dehazing, Confidence prior, Appearance feature
BibRef
Zhao, D.[Dong],
Xu, L.[Long],
Ma, L.[Lin],
Li, J.[Jia],
Yan, Y.H.[Yi-Hua],
Pyramid Global Context Network for Image Dehazing,
CirSysVideo(31), No. 8, August 2021, pp. 3037-3050.
IEEE DOI
2108
Context modeling, Convolution, Atmospheric modeling, Scattering,
Solid modeling, Databases, Estimation, Image dehazing, deep learning,
dilated residual U-Net (DRU)
BibRef
Fujimura, Y.[Yuki],
Sonogashira, M.[Motoharu],
Iiyama, M.[Masaaki],
Dehazing Cost Volume for Deep Multi-View Stereo in Scattering Media
with Airlight and Scattering Coefficient Estimation,
CVIU(211), 2021, pp. 103253.
Elsevier DOI
2110
BibRef
Earlier:
Dehazing Cost Volume for Deep Multi-view Stereo in Scattering Media,
ACCV20(I:261-277).
Springer DOI
2103
Multi-view stereo, Depth estimation, Scattering media,
Airlight, Scattering coefficient
BibRef
Cao, Z.W.[Zhi-Wei],
Qin, Y.[Yong],
Jia, L.M.[Li-Min],
Xie, Z.Y.[Zheng-Yu],
Liu, Q.H.[Qing-Hong],
Ma, X.P.[Xiao-Ping],
Yu, C.C.[Chong-Chong],
Haze Removal of Railway Monitoring Images Using Multi-Scale Residual
Network,
ITS(22), No. 12, December 2021, pp. 7460-7473.
IEEE DOI
2112
Rail transportation, Atmospheric modeling, Monitoring,
Residual neural networks, Training, Image quality,
residual network
BibRef
Wei, H.R.[Hao-Ran],
Wu, Q.[Qingbo],
Li, H.[Hui],
Ngan, K.N.[King Ngi],
Li, H.L.[Hong-Liang],
Meng, F.[Fanman],
Xu, L.F.[Lin-Feng],
Non-Homogeneous Haze Removal via Artificial Scene Prior and
Bidimensional Graph Reasoning,
IP(30), 2021, pp. 9136-9149.
IEEE DOI
2112
Cognition, Atmospheric modeling, Scattering, Logic gates,
Task analysis, Visualization, Image restoration,
bidimensional graph reasoning
BibRef
Ju, M.Y.[Ming-Ye],
Ding, C.[Can],
Guo, C.A.[Charles A.],
Ren, W.Q.[Wen-Qi],
Tao, D.C.[Da-Cheng],
IDRLP: Image Dehazing Using Region Line Prior,
IP(30), 2021, pp. 9043-9057.
IEEE DOI
2112
Atmospheric modeling, Image color analysis, Optimization,
Image restoration, Brightness, Scattering, Interference,
2D joint optimization
BibRef
Guo, J.H.[Jian-Hua],
Yang, J.Y.[Jing-Yu],
Yue, H.J.[Huan-Jing],
Hou, C.P.[Chun-Ping],
Li, K.[Kun],
Landsat-8 OLI Multispectral Image Dehazing Based on Optimized
Atmospheric Scattering Model,
GeoRS(59), No. 12, December 2021, pp. 10255-10265.
IEEE DOI
2112
Atmospheric modeling, Remote sensing, Scattering, Earth,
Artificial satellites, Computational modeling, Atmospheric waves,
wavelength and haze conditions dependence
BibRef
Zhang, X.Q.[Xiao-Qin],
Wang, T.[Tao],
Luo, W.H.[Wen-Han],
Huang, P.C.[Peng-Cheng],
Multi-Level Fusion and Attention-Guided CNN for Image Dehazing,
CirSysVideo(31), No. 11, November 2021, pp. 4162-4173.
IEEE DOI
2112
Atmospheric modeling, Image restoration, Feature extraction,
Convolution, Semantics, Scattering, Task analysis, Image dehazing, CNN,
attention module
BibRef
Jiang, B.[Bo],
Chen, G.[Guanting],
Wang, J.[Jinshuai],
Ma, H.[Hang],
Wang, L.[Lin],
Wang, Y.X.[Yu-Xuan],
Chen, X.X.[Xiao-Xuan],
Deep Dehazing Network for Remote Sensing Image with Non-Uniform Haze,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Ge, W.Y.[Wen-Yi],
Lin, Y.[Yi],
Wang, Z.T.[Zhi-Tao],
Wang, G.G.[Gui-Gui],
Tan, S.H.[Shi-Han],
An Improved U-Net Architecture for Image Dehazing,
IEICE(E104-D), No. 12, December 2021, pp. 2218-2225.
WWW Link.
2112
BibRef
Kumar, A.[Avishek],
Jha, R.K.[Rajib Kumar],
Nishchal, N.K.[Naveen K.],
A multi-exposure fusion framework for contrast enhancement of hazy
images employing dynamic stochastic resonance,
JVCIR(81), 2021, pp. 103376.
Elsevier DOI
2112
Dynamic stochastic resonance, Image dehazing, Restoration,
Weight maps, Multi-scale fusion, Modified atmospheric scattering equation
BibRef
Hodges, C.[Cameron],
Bennamoun, M.[Mohammed],
Boussaid, F.[Farid],
Quantitative performance evaluation of object detectors in hazy
environments,
PRL(152), 2021, pp. 150-157.
Elsevier DOI
2112
Object detection, Deep learning, Haze
BibRef
Huang, S.Q.[Shi-Qi],
Xu, J.[Jie],
Liu, Z.G.[Zhi-Gang],
Sun, K.[Ke],
Lu, Y.[Ying],
Image haze removal based on rolling deep learning and Retinex theory,
IET-IPR(16), No. 2, 2022, pp. 485-498.
DOI Link
2201
BibRef
Shin, J.[Joongchol],
Park, H.[Hasil],
Paik, J.[Joonki],
Region-Based Dehazing via Dual-Supervised Triple-Convolutional
Network,
MultMed(24), 2022, pp. 245-260.
IEEE DOI
2202
Atmospheric modeling, Degradation, Image edge detection,
Brightness, Rail to rail outputs, Neural networks,
self-supervised learning
BibRef
Liu, Y.T.[Yan-Ting],
Yin, H.[Hui],
Wan, J.[Jin],
Liu, Z.H.[Zhi-Hao],
Chong, A.[Aixin],
Edge Aware Network for Image Dehazing,
SPLetters(29), 2022, pp. 174-178.
IEEE DOI
2202
Image edge detection, Feature extraction, Training, Convolution,
Decoding, Task analysis, Image restoration, Image dehazing, edge aware
BibRef
Bai, H.R.[Hao-Ran],
Pan, J.S.[Jin-Shan],
Xiang, X.G.[Xin-Guang],
Tang, J.H.[Jin-Hui],
Self-Guided Image Dehazing Using Progressive Feature Fusion,
IP(31), 2022, pp. 1217-1229.
IEEE DOI
2202
Feature extraction, Image restoration, Atmospheric modeling,
Estimation, Scattering, Image color analysis,
progressive feature fusion
BibRef
Hu, D.S.[Dao-Song],
Yang, Y.[Yang],
Li, B.[Bo],
Tang, H.M.[Hui-Ming],
Xu, Y.[Yu],
Fast outdoor hazy image dehazing based on saturation and brightness,
IET-IPR(16), No. 3, 2022, pp. 900-912.
DOI Link
2202
BibRef
Agrawal, S.C.[Subhash Chand],
Jalal, A.S.[Anand Singh],
Dense Haze Removal by Nonlinear Transformation,
CirSysVideo(32), No. 2, February 2022, pp. 593-607.
IEEE DOI
2202
Image color analysis, Filtering, Nonlinear distortion,
Image restoration, Atmospheric modeling, Scattering, Meteorology,
dense haze
BibRef
Sanwlani, N.[Nivedita],
Das, R.[Reshmi],
Understanding Haze: Modeling Size-Resolved Mineral Aerosol from
Satellite Remote Sensing,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Chen, J.Y.[Ji-You],
Yang, G.[Gaobo],
Ding, X.L.[Xiang-Ling],
Guo, Z.Q.[Zhi-Qing],
Wang, S.[Shuai],
Robust detection of dehazed images via dual-stream CNNs with adaptive
feature fusion,
CVIU(217), 2022, pp. 103357.
Elsevier DOI
2203
Image dehazing detection, Illuminations consistency, Adaptive fusion
BibRef
Kim, G.[Guisik],
Kwon, J.[Junseok],
Deep Illumination-Aware Dehazing With Low-Light and Detail
Enhancement,
ITS(23), No. 3, March 2022, pp. 2494-2508.
IEEE DOI
2203
Lighting, Atmospheric modeling, Estimation, Task analysis,
Image color analysis, Atmospheric measurements, Brightness,
low-light enhancement
BibRef
Zhang, J.[Jiahe],
Min, X.K.[Xiong-Kuo],
Zhu, Y.C.[Yu-Cheng],
Zhai, G.T.[Guang-Tao],
Zhou, J.T.[Jian-Tao],
Yang, X.K.[Xiao-Kang],
Zhang, W.J.[Wen-Jun],
HazDesNet: An End-to-End Network for Haze Density Prediction,
ITS(23), No. 4, April 2022, pp. 3087-3102.
IEEE DOI
2204
Atmospheric modeling, Databases, Meteorology, Training,
Task analysis, Predictive models, Mathematical model,
deep learning
BibRef
Xu, H.Y.[Hao-Yu],
Li, Y.N.[Yue-Nan],
A Deep Neural Network for Coarse-to-Fine Image Dehazing with
Interleaved Residual Connections and Semi-Supervised Training,
IEICE(E105-D), No. 5, May 2022, pp. 1125-1129.
WWW Link.
2205
BibRef
Lee, S.[Seungmin],
Ngo, D.[Dat],
Kang, B.[Bongsoon],
Design of an FPGA-Based High-Quality Real-Time Autonomous Dehazing
System,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link
2205
BibRef
Ma, X.F.[Xiao-Feng],
Wang, Q.M.[Qun-Ming],
Tong, X.H.[Xiao-Hua],
A spectral grouping-based deep learning model for haze removal of
hyperspectral images,
PandRS(188), 2022, pp. 177-189.
Elsevier DOI
2205
Spectral correlation, Haze removal, Hyperspectral images, Deep learning
BibRef
Nie, J.[Jing],
Pang, Y.W.[Yan-Wei],
Xie, J.[Jin],
Pan, J.[Jing],
Han, J.G.[Jun-Gong],
Stereo Refinement Dehazing Network,
CirSysVideo(32), No. 6, June 2022, pp. 3334-3345.
IEEE DOI
2206
Feature extraction, Atmospheric modeling, Task analysis,
Stereo vision, Image restoration, Computational modeling,
channel and spatial refinement
BibRef
Shi, Z.H.[Zheng-Hao],
Shao, S.[Shuai],
Zhou, Z.[Zhaorun],
A saliency guided remote sensing image dehazing network model,
IET-IPR(16), No. 9, 2022, pp. 2483-2494.
DOI Link
2206
BibRef
Lv, J.W.[Jian-Wei],
Qian, F.[Feng],
Zhang, B.[Bao],
Low-light image haze removal with light segmentation and nonlinear
image depth estimation,
IET-IPR(16), No. 10, 2022, pp. 2623-2637.
DOI Link
2207
BibRef
Ju, M.Y.[Ming-Ye],
Ding, C.[Can],
Ren, W.Q.[Wen-Qi],
Yang, Y.[Yi],
IDBP: Image Dehazing Using Blended Priors Including Non-Local, Local,
and Global Priors,
CirSysVideo(32), No. 7, July 2022, pp. 4867-4871.
IEEE DOI
2207
Estimation, Atmospheric modeling, Image color analysis,
Mathematical model, Image restoration, Training, Scattering,
image dehazing
BibRef
Jiao, L.[Libin],
Hu, C.[Changmiao],
Huo, L.[Lianzhi],
Tang, P.[Ping],
Guided-Pix2Pix+: End-to-end spatial and color refinement network for
image dehazing,
SP:IC(107), 2022, pp. 116758.
Elsevier DOI
2208
End-to-end image dehazing, Spatial transmission refinement,
Color refinement, Intensity standardization and outlier-clipping
BibRef
Liu, X.N.[Xiao-Ning],
Li, H.[Hui],
Zhu, C.[Ce],
Joint Contrast Enhancement and Exposure Fusion for Real-World Image
Dehazing,
MultMed(24), 2022, pp. 3934-3946.
IEEE DOI
2208
Image color analysis, Atmospheric modeling, Histograms,
Visualization, Transforms, Scattering, Image enhancement,
image enhancement
BibRef
Roy, S.D.[Sourav Dey],
Bhowmik, M.K.[Mrinal Kanti],
AWDMC-Net: Classification of Adversarial Weather Degraded Multiclass
scenes using a Convolution Neural Network,
CVIU(222), 2022, pp. 103498.
Elsevier DOI
2209
Atmospheric/weather conditions, E-TUVD dataset,
Convolutional Neural Network, Skip connections, Pruning,
Performance evaluation
BibRef
Roy, S.D.[Sourav Dey],
Pal, T.[Tannistha],
Bhowmik, M.K.[Mrinal Kanti],
Benchmarking of Natural Scene Image Dataset In Degraded Conditions
for Visibility Enhancement,
ICIP21(1999-2003)
IEEE DOI
2201
Measurement, Deep learning, Statistical analysis, Image processing,
Lighting, Atmosphere, Atmospheric Conditions,
Quantitative Analysis
BibRef
Zhang, J.G.[Jin-Gang],
Ren, W.Q.[Wen-Qi],
Zhang, S.D.[Sheng-Dong],
Zhang, H.[He],
Nie, Y.F.[Yun-Feng],
Xue, Z.[Zhe],
Cao, X.C.[Xiao-Chun],
Hierarchical Density-Aware Dehazing Network,
Cyber(52), No. 10, October 2022, pp. 11187-11199.
IEEE DOI
2209
Atmospheric modeling, Laplace equations, Feature extraction,
Decoding, Computational modeling, Image resolution, Generators,
hierarchical network
BibRef
Wu, Y.Q.[Yi-Qiang],
Tao, D.P.[Da-Peng],
Zhan, Y.B.[Yi-Bing],
Zhang, C.Y.[Chen-Yang],
BiN-Flow: Bidirectional Normalizing Flow for Robust Image Dehazing,
IP(31), 2022, pp. 6635-6648.
IEEE DOI
2211
Training, Image restoration, Image color analysis,
Band-pass filters, Convolutional neural networks, restoration diversity
BibRef
Si, Y.Z.[Yao-Zhong],
Yang, F.[Fan],
Guo, Y.[Ya],
Zhang, W.[Wei],
Yang, Y.[Yipu],
A comprehensive benchmark analysis for sand dust image reconstruction,
JVCIR(89), 2022, pp. 103638.
Elsevier DOI
2212
Sand dust image, Benchmark dataset, Image reconstruction,
Comprehensive evaluation, Convolutional neural networks
BibRef
Hua, Z.[Zhongwei],
Qi, L.[Lizhe],
Guan, M.[Min],
Su, H.[Hao],
Sun, Y.Q.[Yun-Quan],
Colour balance and contrast stretching for sand-dust image
enhancement,
IET-IPR(16), No. 14, 2022, pp. 3768-3780.
DOI Link
2212
BibRef
Jeong, J.I.[Jaein I.],
Seo, J.[Jisu],
Park, R.J.[Rokjin J.],
Compromised Improvement of Poor Visibility Due to PM Chemical
Composition Changes in South Korea,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Wang, Y.Z.[Yong-Zhen],
Yan, X.F.[Xue-Feng],
Guan, D.H.[Dong-Hai],
Wei, M.Q.[Ming-Qiang],
Chen, Y.P.[Yi-Ping],
Zhang, X.P.[Xiao-Ping],
Li, J.[Jonathan],
Cycle-SNSPGAN: Towards Real-World Image Dehazing via Cycle Spectral
Normalized Soft Likelihood Estimation Patch GAN,
ITS(23), No. 11, November 2022, pp. 20368-20382.
IEEE DOI
2212
Training, Generative adversarial networks, Atmospheric modeling,
Estimation, Image color analysis, Image reconstruction, Scattering,
object detection
BibRef
Wei, J.C.[Jian-Chong],
Wu, Y.[Yi],
Chen, L.[Liang],
Yang, K.[Kunping],
Lian, R.[Renbao],
Zero-Shot Remote Sensing Image Dehazing Based on a Re-Degradation
Haze Imaging Model,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Yu, J.[Jing],
Liang, D.[Deying],
Hang, B.[Bo],
Gao, H.T.[Hong-Tao],
Aerial Image Dehazing Using Reinforcement Learning,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Wang, P.Y.[Peng-Yu],
Zhu, H.Q.[Hong-Qing],
Zhang, H.[Han],
Wang, N.[Nan],
M-CBN: Manifold constrained joint image dehazing and super-resolution
based on chord boosting network,
PR(135), 2023, pp. 109166.
Elsevier DOI
2212
Image dehazing, Chord boosting network, Super-resolution,
Frequency feature cross-collaboration, Manifold constraint
BibRef
Kim, G.[Guisik],
Kwon, J.[Junseok],
Self-Parameter Distillation Dehazing,
IP(32), 2023, pp. 631-642.
IEEE DOI
2301
Knowledge engineering, Training, Task analysis,
Atmospheric modeling, Feature extraction, Backpropagation, deraining
BibRef
Zhang, S.D.[Sheng-Dong],
Ren, W.Q.[Wen-Qi],
Tan, X.[Xin],
Wang, Z.J.[Zhi-Jie],
Liu, Y.[Yong],
Zhang, J.[Jingang],
Zhang, X.Q.[Xiao-Qin],
Cao, X.C.[Xiao-Chun],
Semantic-Aware Dehazing Network With Adaptive Feature Fusion,
Cyber(53), No. 1, January 2023, pp. 454-467.
IEEE DOI
2301
Semantics, Feature extraction, Image segmentation,
Image color analysis, Task analysis, Image reconstruction, semantic aware
BibRef
Huang, Z.L.[Zi-Long],
Jing, H.Y.[Hong-Yuan],
Chen, A.[Aidong],
Hong, C.[Chen],
Shang, X.[Xinna],
Efficient image dehazing algorithm using multiple priors constraints,
JVCIR(90), 2023, pp. 103694.
Elsevier DOI
2301
Image dehazing, Atmospheric scattering model,
Atmospheric light estimation, Multiple prior constraints
BibRef
Si, Y.[Yidan],
Chen, L.[Lin],
Zheng, Z.J.[Zhao-Jun],
Yang, L.[Leiku],
Wang, F.[Fu],
Xu, N.[Na],
Zhang, X.Y.[Xing-Ying],
A Novel Algorithm of Haze Identification Based on FY3D/MERSI-II
Remote Sensing Data,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link
2301
BibRef
Liu, X.H.[Xiao-Hong],
Shi, Z.H.[Zhi-Hao],
Wu, Z.J.[Zi-Jun],
Chen, J.[Jun],
Zhai, G.T.[Guang-Tao],
GridDehazeNet+: An Enhanced Multi-Scale Network with Intra-Task
Knowledge Transfer for Single Image Dehazing,
ITS(24), No. 1, January 2023, pp. 870-884.
IEEE DOI
2301
Atmospheric modeling, Image restoration, Data models,
Task analysis, Knowledge transfer, Estimation, Training,
intra-task knowledge transfer
BibRef
Liu, X.H.[Xiao-Hong],
Ma, Y.R.[Yong-Rui],
Shi, Z.H.[Zhi-Hao],
Chen, J.[Jun],
GridDehazeNet: Attention-Based Multi-Scale Network for Image Dehazing,
ICCV19(7313-7322)
IEEE DOI
2004
convolutional neural nets, feature extraction,
image colour analysis, image restoration, Data models
BibRef
Li, H.Y.[Hong-Yun],
Guo, S.[Siming],
Image Dehazing via Pyramid Exposure Fusion,
ICIVC22(519-522)
IEEE DOI
2301
Image segmentation, Histograms, Image color analysis,
Visual effects, Minimization, Optimization, image dehazing,
multi-scale fusion
BibRef
Chaturvedi, S.S.[Saket S.],
Zhang, L.[Lan],
Yuan, X.Y.[Xiao-Yong],
Pay 'Attention' to Adverse Weather:
Weather-aware Attention-based Object Detection,
ICPR22(4573-4579)
IEEE DOI
2212
Deep learning, Laser radar, Neural networks, Object detection,
Sensor fusion, Logic gates, Feature extraction, Object Detection,
Attention Neural Network
BibRef
Li, R.[Ruyu],
Dong, H.[Hang],
Wang, L.[Li],
Liang, B.[Boyang],
Guo, Y.[Yu],
Wang, F.[Fei],
Frequency-aware Deep Dual-path Feature Enhancement Network for Image
Dehazing,
ICPR22(3406-3412)
IEEE DOI
2212
Degradation, Wavelet domain, Frequency-domain analysis,
Feature extraction, Image restoration, High frequency
BibRef
Ye, T.[Tian],
Zhang, Y.C.[Yun-Chen],
Jiang, M.C.[Ming-Chao],
Chen, L.[Liang],
Liu, Y.[Yun],
Chen, S.X.[Si-Xiang],
Chen, E.[Erkang],
Perceiving and Modeling Density for Image Dehazing,
ECCV22(XIX:130-145).
Springer DOI
2211
BibRef
Yu, H.[Hu],
Zheng, N.[Naishan],
Zhou, M.[Man],
Huang, J.[Jie],
Xiao, Z.[Zeyu],
Zhao, F.[Feng],
Frequency and Spatial Dual Guidance for Image Dehazing,
ECCV22(XIX:181-198).
Springer DOI
2211
BibRef
Jiang, X.Y.[Xing-Yu],
Dou, H.K.[Hong-Kun],
Fu, C.W.[Cheng-Wei],
Dai, B.Q.[Bing-Quan],
Xu, T.R.[Tian-Run],
Deng, Y.[Yue],
Boosting Supervised Dehazing Methods via Bi-level Patch Reweighting,
ECCV22(XVIII:57-73).
Springer DOI
2211
BibRef
Chen, J.[Jiyou],
Wang, S.C.[Sheng-Chun],
Liu, X.[Xin],
Yang, G.[Gaobo],
RW-HAZE: A Real-World Benchmark Dataset to Evaluate Quantitatively
Dehazing Algorithms,
ICIP22(11-15)
IEEE DOI
2211
Urban areas, Benchmark testing, Cameras, Robustness, image dehazing,
benchmark dataset, performance evaluation
BibRef
Laha, S.[Sumit],
Foroosh, H.[Hassan],
Haar Wavelet-Based Attention Network for Image Dehazing,
ICIP22(3948-3952)
IEEE DOI
2211
Visualization, Image color analysis, Statistical analysis,
Refining, Neural networks, Wavelet analysis, Robustness,
convolutional neural networks
BibRef
Luo, X.[Xiongbiao],
Deeply Learned Structure-Aware Transmission for Image Haze Removal,
ICIP22(2056-2060)
IEEE DOI
2211
Photography, Visualization, Uncertainty, Benchmark testing,
Information filters, Image restoration,
computational photography
BibRef
Guo, C.[Chunle],
Yan, Q.X.[Qi-Xin],
Anwar, S.[Saeed],
Cong, R.[Runmin],
Ren, W.Q.[Wen-Qi],
Li, C.Y.[Chong-Yi],
Image Dehazing Transformer with Transmission-Aware 3D Position
Embedding,
CVPR22(5802-5810)
IEEE DOI
2210
Convolution, Modulation, Benchmark testing, Transformers,
Pattern recognition, Low-level vision
BibRef
Yang, Y.[Yang],
Wang, C.[Chaoyue],
Liu, R.[Risheng],
Zhang, L.[Lin],
Guo, X.J.[Xiao-Jie],
Tao, D.C.[Da-Cheng],
Self-augmented Unpaired Image Dehazing via Density and Depth
Decomposition,
CVPR22(2027-2036)
IEEE DOI
2210
Training, Computational modeling, Scattering, Estimation,
Training data, Data models, Low-level vision, Self- semi- meta- unsupervised learning
BibRef
Li, Y.[Yi],
Chang, Y.[Yi],
Gao, Y.[Yan],
Yu, C.F.[Chang-Feng],
Yan, L.X.[Lu-Xin],
Physically Disentangled Intra- and Inter-domain Adaptation for
Varicolored Haze Removal,
CVPR22(5831-5840)
IEEE DOI
2210
Adaptation models, Image color analysis, Atmospheric modeling,
Computational modeling, Scattering, Pattern recognition, Low-level vision
BibRef
Chen, Z.J.[Zhao-Jie],
Li, Q.[Qi],
Feng, H.J.[Hua-Jun],
Xu, Z.H.[Zhi-Hai],
Chen, Y.T.[Yue-Ting],
Nonuniformly Dehaze Network for Visible Remote Sensing Images,
NTIRE22(446-455)
IEEE DOI
2210
Image quality, Fuses, Convolution, Feature extraction, Pattern recognition
BibRef
Tan, L.[Lin],
Wang, S.[Shan],
Zhang, L.[Libao],
Nighttime Haze Removal Using Saliency-Oriented Ambient Light and
Transmission Estimation,
ICIP21(1764-1768)
IEEE DOI
2201
Image color analysis, Lighting, Imaging, Estimation,
Channel estimation, Filtering algorithms, Nighttime haze removal,
fused ambient light
BibRef
Zhang, K.[Kemeng],
Zheng, R.[Ruohui],
Ma, S.[Sijia],
Zhang, L.[Libao],
UAV Remote Sensing Image Dehazing Based on Saliency Guided
Two-Scaletransmission Correction,
ICIP21(2848-2852)
IEEE DOI
2201
Image color analysis, Frequency-domain analysis, Estimation,
Distortion, Visual effects, Propagation losses,
transmission correction
BibRef
Wang, S.[Shan],
Zhang, L.[Libao],
Dynamic Mutual Enhancement Network for Single Remote Sensing Image
Dehazing,
ICIP22(3336-3340)
IEEE DOI
2211
Training, Heuristic algorithms, Semantics, Feature extraction,
Robustness, Decoding, Image restoration, Image enhancement, CNN
BibRef
Wang, S.[Shan],
Wu, H.L.[Han-Lin],
Zhang, L.[Libao],
Afdn: Attention-Based Feedback Dehazing Network for UAV Remote
Sensing Image Haze Removal,
ICIP21(3822-3826)
IEEE DOI
2201
Energy loss, Statistical analysis, Fitting, Feature extraction,
Unmanned aerial vehicles, Surface fitting, Surface texture, CNN
BibRef
Suárez, P.L.[Patricia L.],
Carpio, D.[Dario],
Sappa, A.D.[Angel D.],
Non-homogeneous Haze Removal Through a Multiple Attention Module
Architecture,
ISVC21(II:178-190).
Springer DOI
2112
BibRef
Zheng, Z.R.[Zhuo-Ran],
Ren, W.Q.[Wen-Qi],
Cao, X.C.[Xiao-Chun],
Wang, T.[Tao],
Jia, X.[Xiuyi],
Ultra-High-Definition Image HDR Reconstruction via Collaborative
Bilateral Learning,
ICCV21(4429-4438)
IEEE DOI
2203
Visualization, Image resolution, Image color analysis,
Image edge detection, Reconstruction algorithms, Dynamic range,
Vision for robotics and autonomous vehicles
BibRef
Zheng, Z.R.[Zhuo-Ran],
Ren, W.Q.[Wen-Qi],
Cao, X.C.[Xiao-Chun],
Hu, X.B.[Xia-Bin],
Wang, T.[Tao],
Song, F.L.[Feng-Long],
Jia, X.[Xiuyi],
Ultra-High-Definition Image Dehazing via Multi-Guided Bilateral
Learning,
CVPR21(16180-16189)
IEEE DOI
2111
Training, Image resolution, Image edge detection,
Feature extraction, Real-time systems, Pattern recognition, Image restoration
BibRef
Zhang, X.[Xinyi],
Dong, H.[Hang],
Pan, J.S.[Jin-Shan],
Zhu, C.[Chao],
Tai, Y.[Ying],
Wang, C.J.[Cheng-Jie],
Li, J.L.[Ji-Lin],
Huang, F.Y.[Fei-Yue],
Wang, F.[Fei],
Learning to Restore Hazy Video: A New Real-World Dataset and A New
Method,
CVPR21(9235-9244)
IEEE DOI
2111
Training, Costs, Computational modeling, Redundancy,
Supervised learning, Pattern recognition
BibRef
Chen, Z.Y.[Ze-Yuan],
Wang, Y.C.[Yang-Chao],
Yang, Y.[Yang],
Liu, D.[Dong],
PSD: Principled Synthetic-to-Real Dehazing Guided by Physical Priors,
CVPR21(7176-7185)
IEEE DOI
2111
Training, Measurement, Learning systems, Visualization,
Data models, Pattern recognition
BibRef
Jo, E.[Eunsung],
Sim, J.Y.[Jae-Young],
Multi-Scale Selective Residual Learning for Non-Homogeneous Dehazing,
NTIRE21(507-515)
IEEE DOI
2109
Degradation, Image color analysis, Scattering, Tools, Distortion
BibRef
Chen, T.Y.[Tian-Yi],
Fu, J.H.[Jia-Hui],
Jiang, W.T.[Wen-Tao],
Gao, C.[Chen],
Liu, S.[Si],
SRKTDN: Applying Super Resolution Method to Dehazing Task,
NTIRE21(487-496)
IEEE DOI
2109
Knowledge engineering, Image quality, Computational modeling,
Superresolution, Scattering, Pattern recognition
BibRef
Fu, M.[Minghan],
Liu, H.[Huan],
Yu, Y.[Yankun],
Chen, J.[Jun],
Wang, K.[Keyan],
DW-GAN: A Discrete Wavelet Transform GAN for NonHomogeneous Dehazing,
NTIRE21(203-212)
IEEE DOI
2109
Training, Wavelet domain, Image color analysis,
Frequency-domain analysis, Generative adversarial networks,
Pattern recognition
BibRef
Yu, Y.[Yankun],
Liu, H.[Huan],
Fu, M.[Minghan],
Chen, J.[Jun],
Wang, X.[Xiyao],
Wang, K.[Keyan],
A Two-branch Neural Network for Non-homogeneous Dehazing via Ensemble
Learning,
NTIRE21(193-202)
IEEE DOI
2109
Training, Deep learning, Image color analysis,
Neural networks, Transfer learning, Fitting
BibRef
Ju, M.Y.[Ming-Ye],
Chen, C.H.[Chu-Heng],
Liu, J.P.[Ju-Ping],
Cheng, K.[Kai],
Zhang, D.Y.[Deng-Yin],
VRHI: Visibility Restoration for Hazy Images Using a Haze Density
Model,
UG21(897-904)
IEEE DOI
2109
Training, Image color analysis, Atmospheric modeling, Refining,
Scattering, Predictive models, Distortion
BibRef
Laha, S.[Sumit],
Sharma, A.[Ankit],
Hu, S.N.[Sheng-Nan],
Foroosh, H.[Hassan],
Near-Infrared Depth-Independent Image Dehazing using Haar Wavelets,
ICPR21(5384-5390)
IEEE DOI
2105
Measurement, Image color analysis, Image edge detection,
Scattering, Feature extraction, Image restoration, Data mining, Image fusion
BibRef
Zheng, S.Y.[Shun-Yuan],
Sun, J.[Jiamin],
Liu, Q.L.[Qing-Lin],
Qi, Y.K.[Yuan-Kai],
Zhang, S.P.[Sheng-Ping],
Overwater Image Dehazing via Cycle-consistent Generative Adversarial
Network,
ACCV20(II:251-267).
Springer DOI
2103
BibRef
Zhang, Z.X.[Zheng-Xi],
Zhao, L.[Liang],
Liu, Y.[Yunan],
Zhang, S.S.[Shan-Shan],
Yang, J.[Jian],
Unified Density-aware Image Dehazing and Object Detection in Real-world
Hazy Scenes,
ACCV20(IV:119-135).
Springer DOI
2103
BibRef
Zhang, Y.,
Luo, L.Y.,
Zhao, H.J.,
Qiu, R.D.,
Ying, Y.S.,
Image Dehazing Based on Multispectral Polarization Imaging Method In
Different Detection Modes,
ISPRS20(B1:615-620).
DOI Link
2012
BibRef
Lee, Y.W.,
Wong, L.K.,
See, J.,
Image Dehazing With Contextualized Attentive U-NET,
ICIP20(1068-1072)
IEEE DOI
2011
Convolution, Training, Atmospheric modeling, Visualization,
Feature extraction, Convolutional neural networks,
dilated convolution
BibRef
Jin, Y.,
Gao, G.,
Liu, Q.,
Wang, Y.,
Unsupervised Conditional Disentangle Network For Image Dehazing,
ICIP20(963-967)
IEEE DOI
2011
Atmospheric modeling, Training, Generators, Adaptation models,
Context modeling, GAN
BibRef
Dong, J.X.[Jiang-Xin],
Pan, J.S.[Jin-Shan],
Physics-based Feature Dehazing Networks,
ECCV20(XXX: 188-204).
Springer DOI
2010
BibRef
El Khoury, J.[Jessica],
Thomas, J.B.[Jean-Baptiste],
Mansouri, A.[Alamin],
A Spectral Hazy Image Database,
ICISP20(44-53).
Springer DOI
2009
BibRef
Ancuti, C.O.[Codruta O.],
Ancuti, C.[Cosmin],
Vasluianu, F.A.[Florin-Alexandru],
Timofte, R.[Radu],
Fu, M.[Minghan],
Liu, H.[Huan],
Yu, Y.[Yankun],
Chen, J.[Jun],
Wang, K.[Keyan],
Chang, J.[Jerome],
Wang, X.[Xiyao],
Liu, J.[Jing],
Xu, Y.[Yi],
Zhang, X.J.[Xin-Jian],
Zhao, M.[Minyi],
Zhou, S.G.[Shui-Geng],
Chen, T.Y.[Tian-Yi],
Fu, J.H.[Jia-Hui],
Jiang, W.T.[Wen-Tao],
Gao, C.[Chen],
Liu, S.[Si],
Wang, Y.D.[Yu-Dong],
Guo, J.C.[Ji-Chang],
Li, C.Y.[Chong-Yi],
Yan, Q.[Qixin],
Zheng, S.[Sida],
Zamir, S.W.[Syed Waqas],
Arora, A.[Aditya],
Dudhane, A.[Akshay],
Khan, S.[Salman],
Hayat, M.[Munawar],
Khan, F.S.[Fahad Shahbaz],
Shao, L.[Ling],
Zhang, H.C.[Hai-Chuan],
Guo, T.[Tiantong],
Monga, V.[Vishal],
Yang, W.J.[Wen-Jin],
Lin, J.[Jin],
Luo, X.T.[Xiao-Tong],
Huang, G.[Guowen],
Chen, S.[Shuxin],
Qu, Y.Y.[Yan-Yun],
Xu, K.[Kele],
Yang, L.[Lehan],
Sun, P.L.[Peng-Liang],
Niu, X.T.[Xue-Tong],
Zheng, J.J.[Jun-Jun],
Ruan, X.T.[Xiao-Tong],
Wang, Y.F.[Yun-Feng],
Yang, J.[Jiang],
Luo, Z.P.[Zhi-Peng],
Wang, S.[Sai],
Xu, Z.Y.[Zhen-Yu],
Cao, X.C.[Xiao-Chun],
Luo, J.[Jun],
Zheng, Z.R.[Zhuo-Ran],
Ren, W.Q.[Wen-Qi],
Wang, T.[Tao],
Chen, Y.Q.[Yi-Qun],
Leng, C.[Cong],
Li, C.H.[Cheng-Hua],
Cheng, J.[Jian],
Sung, C.S.[Chang-Sung],
Chen, J.C.[Jun-Cheng],
Jo, E.[Eunsung],
Sim, J.Y.[Jae-Young],
Geethu, M.M.,
Akhil, K.A.,
Sreeni, K.G.,
Jeena, R.S.,
Zacharias, J.[Joseph],
Manu, C.M.[Chippy M],
Huang, Z.X.[Ze-Xi],
Zhang, B.F.[Bao-Feng],
Zhang, Y.[Yiwen],
Li, J.D.[Jin-Dong],
Chen, M.[Mianjie],
Xiao, Q.[Quan],
Su, Q.C.[Qing-Chao],
Han, L.H.[Li-Hua],
Huang, Y.T.[Yan-Ting],
Prajapati, K.[Kalpesh],
Chudasama, V.[Vishal],
Patel, H.[Heena],
Sarvaiya, A.[Anjali],
Upla, K.[Kishor],
Raja, K.[Kiran],
Ramachandra, R.[Raghavendra],
Busch, C.[Christoph],
Jing, H.Y.[Hong-Yuan],
Huang, Z.L.[Zi-Long],
Fu, Y.[Yiran],
Wu, H.Q.[Hao-Qiang],
Zha, Q.X.[Quan-Xing],
Zhu, Z.W.[Zhi-Wei],
Lv, H.[Hejun],
NTIRE 2021 NonHomogeneous Dehazing Challenge Report,
NTIRE21(627-646)
IEEE DOI
2109
Correlation, Architecture,
Pattern recognition, Testing
BibRef
Ancuti, C.O.[Codruta O.],
Ancuti, C.[Cosmin],
Vasluianu, F.A.[Florin-Alexandru],
Timofte, R.[Radu],
Liu, J.[Jing],
Wu, H.Y.[Hai-Yan],
Xie, Y.[Yuan],
Qu, Y.Y.[Yan-Yun],
Ma, L.Z.[Li-Zhuang],
Huang, Z.L.[Zi-Ling],
Deng, Q.[Qili],
Chao, J.C.[Ju-Chin],
Yang, T.S.[Tsung-Shan],
Chen, P.W.[Peng-Wen],
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Sun, C.E.[Chung-En],
Wu, P.Y.[Pei-Yuan],
Do, J.[Jeonghyeok],
Park, J.M.[Jong-Min],
Kim, M.C.[Mun-Churl],
Metwaly, K.[Kareem],
Li, X.L.[Xue-Lu],
Guo, T.T.[Tian-Tong],
Monga, V.[Vishal],
Yu, M.Z.[Ming-Zhao],
Cherukuri, V.[Venkateswararao],
Chuang, S.Y.[Shiue-Yuan],
Lin, T.N.[Tsung-Nan],
Lee, D.[David],
Chang, J.[Jerome],
Wang, Z.H.[Zhan-Han],
Chang, Y.B.[Yu-Bang],
Lin, C.H.[Chang-Hong],
Dong, Y.[Yu],
Zhou, H.Y.[Hong-Yu],
Kong, X.Z.[Xiang-Zhen],
Das, S.D.[Sourya Dipta],
Dutta, S.[Saikat],
Zhao, X.[Xuan],
Ouyang, B.[Bing],
Estrada, D.[Dennis],
Wang, M.Q.[Mei-Qi],
Su, T.Q.[Tian-Qi],
Chen, S.[Siyi],
Sun, B.Y.[Bang-Yong],
Whannou de Dravo, V.[Vincent],
Yu, Z.[Zhe],
Narang, P.[Pratik],
Mehra, A.[Aryan],
Raghunath, N.[Navaneeth],
Mandal, M.[Murari],
NTIRE 2020 Challenge on NonHomogeneous Dehazing,
NTIRE20(2029-2044)
IEEE DOI
2008
Cameras, Image restoration, Image resolution, Benchmark testing,
Image color analysis, Runtime, Sun
BibRef
Kumar, P.,
Priyankar, S.,
Sur, J.A.,
Scale-aware Conditional Generative Adversarial Network for Image
Dehazing,
WACV20(2344-2354)
IEEE DOI
2006
Image color analysis, Kernel, Task analysis, Laplace equations,
Training, Generative adversarial networks, Cost function
BibRef
Li, Y.,
Miao, Q.,
Ouyang, W.,
Ma, Z.,
Fang, H.,
Dong, C.,
Quan, Y.,
LAP-Net: Level-Aware Progressive Network for Image Dehazing,
ICCV19(3275-3284)
IEEE DOI
2004
image colour analysis, image denoising, image enhancement,
image restoration, learning (artificial intelligence),
Fuses
BibRef
Liu, Y.,
Pan, J.,
Ren, J.,
Su, Z.,
Learning Deep Priors for Image Dehazing,
ICCV19(2492-2500)
IEEE DOI
2004
gradient methods, image colour analysis, image denoising,
image enhancement, image restoration, iterative methods,
Machine learning
BibRef
Gandelsman, Y.[Yosef],
Shocher, A.[Assaf],
Irani, M.[Michal],
'Double-DIP': Unsupervised Image Decomposition via Coupled
Deep-Image-Priors,
CVPR19(11018-11027).
IEEE DOI
2002
Decompose image into 2 layers, e.g. clear image and haze.
BibRef
Qu, Y.Y.[Yan-Yun],
Chen, Y.Z.[Yi-Zi],
Huang, J.Y.[Jing-Ying],
Xie, Y.[Yuan],
Enhanced Pix2pix Dehazing Network,
CVPR19(8152-8160).
IEEE DOI
2002
BibRef
Shu, Q.,
Wu, C.,
Xiao, Z.,
Liu, R.W.,
Variational Regularized Transmission Refinement for Image Dehazing,
ICIP19(2781-2785)
IEEE DOI
1910
Dehazing, image restoration, dark channel prior, total variation,
alternating direction algorithm
BibRef
Mei, K.F.[Kang-Fu],
Jiang, A.[Aiwen],
Li, J.C.[Jun-Cheng],
Wang, M.W.[Ming-Wen],
Progressive Feature Fusion Network for Realistic Image Dehazing,
ACCV18(I:203-215).
Springer DOI
1906
BibRef
Maeda, K.[Koushirou],
Hirai, K.[Keita],
Horiuchi, T.[Takahiko],
Haze Transfer Between Images Based on Dark Channel Prior,
CCIW19(221-232).
Springer DOI
1905
BibRef
Vazquez-Corral, J.[Javier],
Finlayson, G.D.[Graham D.],
Bertalmío, M.[Marcelo],
Physically Plausible Dehazing for Non-physical Dehazing Algorithms,
CCIW19(233-244).
Springer DOI
1905
BibRef
Chen, D.,
He, M.,
Fan, Q.,
Liao, J.,
Zhang, L.,
Hou, D.,
Yuan, L.,
Hua, G.,
Gated Context Aggregation Network for Image Dehazing and Deraining,
WACV19(1375-1383)
IEEE DOI
1904
image denoising, image restoration, handcrafted image,
haze-free image, smoothed dilation technique,
Image restoration
BibRef
Galdran, A.,
Bria, A.,
Alvarez-Gila, A.,
Vazquez-Corral, J.,
Bertalmío, M.,
On the Duality Between Retinex and Image Dehazing,
CVPR18(8212-8221)
IEEE DOI
1812
Image color analysis, Task analysis, Atmospheric modeling,
Computational modeling, Lighting
BibRef
Zhang, H.,
Patel, V.M.,
Densely Connected Pyramid Dehazing Network,
CVPR18(3194-3203)
IEEE DOI
1812
Atmospheric modeling, Estimation, Degradation,
Generative adversarial networks, Optimization, Image edge detection
BibRef
Ancuti, C.[Cosmin],
Ancuti, C.O.[Codruta O.],
Timofte, R.[Radu],
Van Gool, L.J.,
Zhang, L.,
Yang, M.,
NTIRE 2018 Challenge on Image Dehazing: Methods and Results,
Restoration18(1004-100410)
IEEE DOI
1812
Image color analysis, Cameras, Image restoration, Lighting,
Generators, Meters, Manuals
See also NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results.
BibRef
Ancuti, C.O.,
Ancuti, C.,
Timofte, R.,
NH-HAZE: An Image Dehazing Benchmark with Non-Homogeneous Hazy and
Haze-Free Images,
NTIRE20(1798-1805)
IEEE DOI
2008
Image color analysis, Optical imaging, Cameras,
Generators, Atmospheric modeling, Benchmark testing
BibRef
Ancuti, C.O.[Codruta O.],
Ancuti, C.[Cosmin],
Sbert, M.,
Timofte, R.[Radu],
Dense-Haze: A Benchmark for Image Dehazing with Dense-Haze and
Haze-Free Images,
ICIP19(1014-1018)
IEEE DOI
1910
BibRef
Ancuti, C.O.[Codruta O.],
Ancuti, C.[Cosmin],
Timofte, R.[Radu],
de Vleeschouwer, C.[Christophe],
O-HAZE: A Dehazing Benchmark with Real Hazy and Haze-Free Outdoor
Images,
Restoration18(867-8678)
IEEE DOI
1812
BibRef
And: A2, A1, A3, A4:
I-HAZE: A Dehazing Benchmark with Real Hazy and Haze-Free Indoor Images,
ACIVS18(620-631).
Springer DOI
1810
Atmospheric modeling, Image color analysis, Cameras, Lighting,
Measurement, Databases, Optical imaging
BibRef
Pei, Y.T.[Yan-Ting],
Huang, Y.P.[Ya-Ping],
Zou, Q.[Qi],
Lu, Y.H.[Yu-Hang],
Wang, S.[Song],
Does Haze Removal Help CNN-Based Image Classification?,
ECCV18(X: 697-712).
Springer DOI
1810
BibRef
Chen, W.,
Yuan, S.,
Tsai, G.,
Wang, H.,
Kuo, S.,
Color Channel-Based Smoke Removal Algorithm Using Machine Learning
for Static Images,
ICIP18(2855-2859)
IEEE DOI
1809
Feature extraction, Image color analysis,
Machine learning algorithms, Atmospheric modeling,
Static Image
BibRef
Kim, G.,
Ha, S.,
Kwon, J.,
Adaptive Patch Based Convolutional Neural Network for Robust Dehazing,
ICIP18(2845-2849)
IEEE DOI
1809
Atmospheric modeling, Machine learning, Adaptive systems,
Estimation, Training, Convolutional neural networks, Robustness,
Quad-tree Decomposition
BibRef
Ancuti, C.O.,
Ancuti, C.,
de Vleeschouwer, C.,
Effective Local Airlight Estimation for Image Dehazing,
ICIP18(2850-2854)
IEEE DOI
1809
Atmospheric modeling, Image color analysis, Estimation,
Computational modeling, Channel estimation, Integrated optics,
hazy
BibRef
Zhang, S.[Siyu],
Li, C.[Congli],
Xue, S.[Song],
Fast Haze Removal of UAV Images Based on Dark Channel Prior,
PSIVTWS17(254-267).
Springer DOI
1806
BibRef
Li, Y.F.[Yu-Fei],
Wang, K.Y.[Ke-Yan],
Xu, N.[Ning],
Li, Y.S.[Yun-Song],
Quantitative evaluation for dehazing algorithms on synthetic outdoor
hazy dataset,
VCIP17(1-4)
IEEE DOI
1804
image enhancement, image restoration, depth estimation method,
depth maps, ground truth reference images,
sky segmentation
BibRef
Lin, K.E.,
Shih, K.T.,
Chen, H.,
Enhancing the perception of a hazy visual world using a see-through
head-mounted device,
ICIP17(4397-4401)
IEEE DOI
1803
Atmosphere, Indexes, Integrated circuits, Optics,
Pattern analysis, Scattering, See-through head-mounted display,
just-noticeable difference
BibRef
Li, B.,
Peng, X.,
Wang, Z.,
Xu, J.,
Feng, D.,
AOD-Net: All-in-One Dehazing Network,
ICCV17(4780-4788)
IEEE DOI
1802
image denoising, image enhancement, neural nets, object detection,
AOD-Net, Faster R-CNN, PSNR, SSIM, all-in-one dehazing network,
Visualization
BibRef
Liu, S.L.[Shi-Long],
Wu, H.K.[Hong-Kun],
Li, R.W.[Ruo-Wei],
Rahman, M.A.[M. Arifur],
He, X.[Xuan],
Liu, S.C.[San-Chi],
Kwok, N.M.[Ngai Ming],
Image De-hazing Based on Polynomial Estimation and Steepest Descent
Concept,
ICVISP17(63-70)
IEEE DOI
1712
Atmospheric modeling, Attenuation, Channel estimation,
Digital images, Distortion, Estimation, Image color analysis,
steepest descent
BibRef
Zhang, J.,
Cao, Y.,
Fang, S.,
Kang, Y.,
Chen, C.W.,
Fast Haze Removal for Nighttime Image Using Maximum Reflectance Prior,
CVPR17(7016-7024)
IEEE DOI
1711
Atmospheric modeling, Attenuation, Image color analysis, Imaging,
Integrated circuit modeling, Light sources, Lighting
BibRef
Jin, X.,
Wang, X.,
Xu, X.,
Yi, C.T.[Cheng-Tao],
Yang, C.Q.[Chang-Qing],
Tensor-based weighted least square decomposition haze removal
algorithm,
ICIVC17(1097-1101)
IEEE DOI
1708
Image restoration, Robustness, Smoothing methods, image dehazing,
nonlinear structure tensor, weighted, least, square, decomposition
BibRef
Santra, S.,
Chanda, B.,
Day/night unconstrained image dehazing,
ICPR16(1406-1411)
IEEE DOI
1705
Aerosols, Atmospheric modeling, Computational modeling,
Image color analysis, Imaging, Mathematical model, Observers,
daytime, image dehazing, night-time
BibRef
Chen, C.[Chen],
Do, M.N.[Minh N.],
Wang, J.[Jue],
Robust Image and Video Dehazing with Visual Artifact Suppression via
Gradient Residual Minimization,
ECCV16(II: 576-591).
Springer DOI
1611
BibRef
Ancuti, C.,
Ancuti, C.O.,
de Vleeschouwer, C.,
D-HAZY: A dataset to evaluate quantitatively dehazing algorithms,
ICIP16(2226-2230)
IEEE DOI
1610
Atmospheric modeling
BibRef
Park, J.,
Kim, K.,
Lee, S.,
Won, C.S.,
Jung, S.W.,
Text-aware image dehazing using stroke width transform,
ICIP16(2231-2235)
IEEE DOI
1610
Channel estimation
BibRef
Han, X.X.[Xiao-Xu],
Feng, H.W.[Hong-Wei],
Bu, Q.R.[Qi-Rong],
Feng, J.[Jun],
Liu, X.N.[Xiao-Ning],
Image dehazing base on two-peak channel prior,
ICIP16(2236-2240)
IEEE DOI
1610
dehazing
BibRef
Wang, W.,
Yuan, X.,
Wu, X.,
Liu, Y.,
Ghanbarzadeh, S.,
An efficient method for image dehazing,
ICIP16(2241-2245)
IEEE DOI
1610
Atmospheric modeling
BibRef
He, J.,
Zhang, C.,
Yang, R.,
Zhu, K.,
Convex optimization for fast image dehazing,
ICIP16(2246-2250)
IEEE DOI
1610
Atmospheric modeling
BibRef
Bhattacharya, S.,
Gupta, S.,
Venkatesh, K.S.,
Dehazing of color image using stochastic enhancement,
ICIP16(2251-2255)
IEEE DOI
1610
Atmospheric modeling
BibRef
Ancuti, C.,
Ancuti, C.O.,
de Vleeschouwer, C.,
Bovik, A.C.,
Night-time dehazing by fusion,
ICIP16(2256-2260)
IEEE DOI
1610
Atmospheric modeling
BibRef
Zhou, Y.[Yang],
Xu, Q.[Qing],
Xu, J.W.[Ji-Wei],
Jin, G.W.[Guo-Wang],
Optical Remote Sensing Image Optimized Dehazing Algorithm Based on Hot,
ISPRS16(B3: 797-803).
DOI Link
1610
BibRef
El Khoury, J.[Jessica],
Thomas, J.B.[Jean-Baptiste],
Mansouri, A.[Alamin],
A Color Image Database for Haze Model and Dehazing Methods Evaluation,
ICISP16(109-117).
WWW Link.
1606
BibRef
Wan, Y.,
Chen, Q.,
Joint image dehazing and contrast enhancement using the HSV color
space,
VCIP15(1-4)
IEEE DOI
1605
Channel estimation
BibRef
Shi, W.Z.[Wu-Zhen],
Gao, X.W.[Xin-Wei],
Chen, B.Q.[Bo-Qi],
Jiang, F.[Feng],
Zhao, D.B.[De-Bin],
Reference image based method of region of interest enhancement for
haze image,
ICIP15(735-739)
IEEE DOI
1512
Region of interest, dark channel prior, dehazing, image enhancement
BibRef
Shen, Y.X.[Yu-Xiang],
Wu, X.L.[Xiao-Lin],
Deng, X.W.[Xiao-Wei],
Analysis on spectral effects of dark-channel prior for haze removal,
ICIP15(2945-2949)
IEEE DOI
1512
HSI color space
BibRef
Zhao, L.Y.[Ling-Yun],
Hansard, M.[Miles],
Cavallaro, A.[Andrea],
Pop-up Modelling of Hazy Scenes,
CIAP15(I:306-318).
Springer DOI
1511
Depth from dehazing.
BibRef
Zhang, J.[Jing],
Cao, Y.[Yang],
Wang, Z.F.[Zeng-Fu],
Nighttime haze removal based on a new imaging model,
ICIP14(4557-4561)
IEEE DOI
1502
Atmospheric modeling
BibRef
He, J.X.[Jia-Xi],
Zhang, C.[Cishen],
Baqee, I.A.[Ifat-Al],
Image Dehazing Using Regularized Optimization,
ISVC14(I: 87-96).
Springer DOI
1501
BibRef
Arigela, S.[Saibabu],
Asari, V.K.[Vijayan K.],
Enhancement of Hazy Color Images Using a Self-Tunable Transformation
Function,
ISVC14(II: 578-587).
Springer DOI
1501
BibRef
Tang, K.[Ketan],
Yang, J.C.[Jian-Chao],
Wang, J.[Jue],
Investigating Haze-Relevant Features in a Learning Framework for
Image Dehazing,
CVPR14(2995-3002)
IEEE DOI
1409
BibRef
Pei, S.C.[Soo-Chang],
Lee, T.Y.[Tzu-Yen],
Nighttime haze removal using color transfer pre-processing and Dark
Channel Prior,
ICIP12(957-960).
IEEE DOI
1302
BibRef
Joshi, N.,
Cohen, M.F.,
Seeing Mt. Rainier: Lucky imaging for multi-image denoising,
sharpening, and haze removal,
ICCP10(1-8).
IEEE DOI
1208
BibRef
Yu, X.L.[Xiao-Liang],
Xiao, C.B.[Chuang-Bai],
Deng, M.[Mike],
Peng, L.[Li],
A Classification Algorithm to Distinguish Image as Haze or Non-haze,
ICIG11(286-289).
IEEE DOI
1109
BibRef
Feng, C.[Chen],
Zhuo, S.J.[Shao-Jie],
Zhang, X.P.[Xiao-Peng],
Shen, L.[Liang],
Susstrunk, S.[Sabine],
Near-infrared guided color image dehazing,
ICIP13(2363-2367)
IEEE DOI
1402
Airlight color, Detail transfer, Image dehazing, NIR, Optimization, RGB
BibRef
Schaul, L.[Lex],
Fredembach, C.[Clement],
Susstrunk, S.[Sabine],
Color image dehazing using the near-infrared,
ICIP09(1629-1632).
IEEE DOI
0911
BibRef
Chapter on Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar continues in
Single Image Dehazing .