19.4.3.22 Super Resolution, Restoration, for Atmosphere Effects, Turbulence

McGlamery, B.L.,
Restoration of Turbulence Degraded Images,
JOSA(57), No. 3, March 1967, pp. 278-299. BibRef 6703

Moldon, J.C.[John C.],
High Resolution Image Estimation in a Turbulent Environment,
PR(2), No. 2, May 1970, pp. 79-82.
Elsevier DOI BibRef 7005

Tolkova, E.,
High-Order Correlation Technique for Imaging Through Turbulence,
OptEng(36), No. 9, September 1997, pp. 2400-2408. 9710
BibRef

Erickson, J.M.[John M.], Crichton, P.B.[Philip B.],
Image stabilization apparatus for telescopic devices,
US_Patent5,596,365, Jan 21, 1997
WWW Link. BibRef 9701

Yitzhaky, Y., Dror, I., Kopeika, N.S.,
Restoration of Atmospherically Blurred Images According to Weather Predicted Atmospheric Modulation Transfer Functions,
OptEng(36), No. 11, November 1997, pp. 3064-3072. 9712
BibRef

Yitzhaky, Y., Mor, I., Lantzman, A., Kopeika, N.S.,
Direct Method for Restoration of Motion Blurred Images,
JOSA-A(15), No. 6, June 1998, pp. 1512-1519. 9806
BibRef

Hadar, O., Adar, Z., Cotter, A., Yitzhaky, Y., Kopeika, N.S.,
Restoration of images degraded by mechanical vibrations,
ICPR94(C:137-139).
IEEE DOI 9410
BibRef

Gerwe, D.R., Plonus, M.A.,
Superresolved Image-Reconstruction of Images Taken Through the Turbulent Atmosphere,
JOSA-A(15), No. 10, October 1998, pp. 2620-2628. 9810
BibRef

Gerwe, D.R., Plonus, M.A.,
Image-Restoration of Multiple Noisy Images by Use of a Priori Knowledge of the Anisoplanatic Point-Spread Function,
Optics Letters(23), No. 2, January 15 1998, pp. 83-85. 9801
BibRef

Cohen, B., Avrin, V., Belitsky, M., Dinstein, I.,
Generation of a Restored Image from a Video Sequence Recorded under Turbulence Effects,
OptEng(36), No. 12, December 1997, pp. 3312-3317. 9801
BibRef

Sheppard, D.G., Hunt, B.R., and Marcellin, M.W.,
Iterative multiframe superresolution algorithms for atmospheric-turbulence-degraded imagery,
JOSA-A(15), No. 5, May 1998, pp. 978-992. BibRef 9805

Fraser, D.[Donald], Thorpe, G.[Glen], Lambert, A.[Andrew],
Atmospheric turbulence visualization with wide-area motion-blur restoration,
JOSA-A(16), No. 7, July 1999, pp. 1751-1758. BibRef 9907
Earlier: A3, A1, A2:
Atmospheric Turbulence Visualisation Through Image Time-Sequence Registration,
ICPR98(Vol II: 1768-1770).
IEEE DOI 9808
BibRef

Wen, Z.Y., Fraser, D.[Donald], Lambert, A.[Andrew],
Bicoherence Used to Predict Lucky Regions in Turbulence Affected Surveillance,
AVSBS06(108-108).
IEEE DOI 0611
BibRef

Wen, Z.Y., Fraser, D.[Donald], Lambert, A.[Andrew], Li, H.D.,
Reconstruction of Underwater Image by Bispectrum,
ICIP07(III: 545-548).
IEEE DOI 0709
BibRef

Sheppard, D.G., Panchapakesan, K., Bligin, A., Hunt, B.R., Marcellin, M.W.,
Lapped Nonlinear Interpolative Vector Quantization and Image Super-Resolution,
IP(9), No. 2, February 2000, pp. 295-298.
IEEE DOI 0003
BibRef

Wang, Y.M.[Yuan-Mei], Gong, X.[Xing],
A neural network approach to microwave imaging,
IJIST(11), No. 3, 2000, pp. 159-163. 0102
BibRef

Wang, Y.M.[Yuan-Mei],
Multicriteria second-order neural networks approach to imaging through turbulence,
IJIST(13), No. 2, 2003, pp. 146-151.
WWW Link. 0308
BibRef

Du, Y.[Yong], Guindon, B., Cihlar, J.,
Haze detection and removal in high resolution satellite image with wavelet analysis,
GeoRS(40), No. 1, January 2002, pp. 210-217.
IEEE Top Reference. 0203
BibRef

Zhang, Y.[Ying], Guindon, B.,
Quantitative assessment of a haze suppression methodology for satellite imagery: effect on land cover classification performance,
GeoRS(41), No. 5, May 2003, pp. 1082-1089.
IEEE Abstract. 0307
BibRef

Shacham, O.[Omri], Haik, O.[Oren], Yitzhaky, Y.[Yitzhak],
Blind restoration of atmospherically degraded images by automatic best step-edge detection,
PRL(28), No. 15, 1 November 2007, pp. 2094-2103.
Elsevier DOI 0711
Step-edge detection, Blind image restoration; Blur identification, Atmospheric blur BibRef

Johnson, P.M.[Peter M.], Goda, M.E.[Matthew E.], Gamiz, V.L.[Victor L.],
Multiframe phase-diversity algorithm for active imaging,
JOSA-A(24), No. 7, July 2007, pp. 1894-1900.
WWW Link. 0801
Imaging through the turbulent atmosphere. BibRef

Metari, S.[Samy], Deschênes, F.[François],
New Classes of Radiometric and Combined Radiometric-Geometric Invariant Descriptors,
IP(17), No. 6, June 2008, pp. 991-1006.
IEEE DOI 0711
BibRef
Earlier:
A New Convolution Kernel for Atmospheric Point Spread Function Applied to Computer Vision,
ICCV07(1-8).
IEEE DOI 0710
BibRef

Metari, S.[Samy], Deschênes, F.[François],
A Novel Polychromatic Model for Light Dispersion,
ICISP10(471-478).
Springer DOI 1006
BibRef

Liu, C.S.[Chun-Sheng], Zhang, T.X.[Tian-Xu], Zhang, B.Y.[Bi-Yin],
Turbulence Degraded Images Restoration Based On Improved Multiframe Iterative Loops And Data Mining,
IJIG(7), No. 3, July 2007, pp. 515-527. 0707
BibRef

Garnier, J.[Josselin], Papanicolaou, G.[George],
Passive Sensor Imaging Using Cross Correlations of Noisy Signals in a Scattering Medium,
SIIMS(2), No. 2, 2009, pp. 396-437.
DOI Link travel time estimation, passive sensor imaging, noise sources, random media BibRef 0900

Garnier, J.[Josselin], Papanicolaou, G.[George], Semin, A.[Adrien], Tsogka, C.[Chrysoula],
Signal-to-Noise Ratio Estimation in Passive Correlation-Based Imaging,
SIIMS(6), No. 2, 2013, pp. 1092-1110.
DOI Link 1307
Stabilization. BibRef

Garnier, J.[Josselin], Papanicolaou, G.[George], Semin, A.[Adrien], Tsogka, C.[Chrysoula],
Signal to Noise Ratio Analysis in Virtual Source Array Imaging,
SIIMS(8), No. 1, 2015, pp. 248-279.
DOI Link 1503
BibRef

Garnier, J.[Josselin], Papanicolaou, G.[George],
Role of Scattering in Virtual Source Array Imaging,
SIIMS(7), No. 2, 2014, pp. 1210-1236.
DOI Link 1407
BibRef

Garnier, J.[Josselin], Papanicolaou, G.[George],
Passive Synthetic Aperture Imaging,
SIIMS(8), No. 4, 2015, pp. 2683-2705.
DOI Link 1601
BibRef

Lemaitre, M.[Magali], Laligant, O.[Olivier], Blanc-Talon, J.[Jacques], Mériaudeau, F.[Fabrice],
Restoration of Videos Degraded by Local Isoplanatism Effects in the Near-Infrared Domain,
ELCVIA(7), No. 3, 2008, pp. xx-yy.
DOI Link 0909
BibRef
Earlier:
Atmospheric Turbulence Effects Removal on Infrared Sequences Degraded by Local Isoplanatism,
IbPRIA07(II: 274-281).
Springer DOI 0706
BibRef

Li, F.[Feng], Jia, X.P.[Xiu-Ping], Fraser, D.[Donald], Lambert, A.[Andrew],
Super Resolution for Remote Sensing Images Based on a Universal Hidden Markov Tree Model,
GeoRS(48), No. 3, March 2010, pp. 1270-1278.
IEEE DOI 1003
BibRef
Earlier: A1, A2, A3, Only:
Universal HMT Based Super Resolution for Remote Sensing Images,
ICIP08(333-336).
IEEE DOI 0810
BibRef

Zhang, G.Y.[Guang-Yun], Jia, X.P.[Xiu-Ping], Hu, J.K.[Jian-Kun],
Superpixel-Based Graphical Model for Remote Sensing Image Mapping,
GeoRS(53), No. 11, November 2015, pp. 5861-5871.
IEEE DOI 1509
geophysical image processing
See also Multi-Resolution Weed Classification via Convolutional Neural Network and Superpixel Based Local Binary Pattern Using Remote Sensing Images. BibRef

Wen, Z.Y.[Zhi-Ying], Li, F.[Feng], Fraser, D.[Donald], Lambert, A.[Andrew], Jia, X.P.[Xiu-Ping],
A Super Resolution Algorithm for Atmospherically Degraded Images Using Lucky Regions and MAP-uHMT,
DICTA09(374-380).
IEEE DOI 0912
BibRef

Molodij, G.[Guillaume], Keil, S.[Steve], Roudier, T.[Thierry], Meunier, N.[Nadège], Rondi, S.[Sylvain],
A method for single image restoration based on the principal ergodic,
JOSA-A(27), No. 11, November 2010, pp. 2459-2467.
WWW Link. 1011
Extract both the object and the point spread function. Apply to atmospheric turbulence. BibRef

Hyde, M.W., Cain, S.C., Schmidt, J.D., Havrilla, M.J.,
Material Classification of an Unknown Object Using Turbulence-Degraded Polarimetric Imagery,
GeoRS(49), No. 1, January 2011, pp. 264-276.
IEEE DOI 1101
Whether metalic or dielectric. LeMaster and Cain:
See also Multichannel blind deconvolution of polarimetric imagery. to remove atmospheric distortion. BibRef

van Eekeren, A.[Adam], Schutte, K.[Klamer], Schwering, P.[Piet],
Turbulence compensation enhances long-range imagery,
SPIE(Newsroom), October 16, 2012
DOI Link 1211
Results:
WWW Link. A novel software method enhances camera images blurred by the atmosphere. BibRef

Zhu, X.[Xiang], Milanfar, P.[Peyman],
Removing Atmospheric Turbulence via Space-Invariant Deconvolution,
PAMI(35), No. 1, January 2013, pp. 157-170.
IEEE DOI 1212
BibRef

Zhu, X.[Xiang], Šroubek, F.[Filip], Milanfar, P.[Peyman],
Deconvolving PSFs for a Better Motion Deblurring Using Multiple Images,
ECCV12(V: 636-647).
Springer DOI 1210
BibRef

Farsiu, S.[Sina], Milanfar, P.[Peyman],
Multi-Scale Statistical Detection and Ballistic Imaging Through Turbid Media,
ICIP07(III: 537-540).
IEEE DOI 0709
BibRef

Alterman, M.[Marina], Schechner, Y.Y.[Yoav Y.], Perona, P.[Pietro], Shamir, J.[Joseph],
Detecting Motion through Dynamic Refraction,
PAMI(35), No. 1, January 2013, pp. 245-251.
IEEE DOI 1212
Refractions from atmospheric turbulence and water surface. BibRef

Anantrasirichai, N., Achim, A., Kingsbury, N.G., Bull, D.R.,
Atmospheric Turbulence Mitigation Using Complex Wavelet-Based Fusion,
IP(22), No. 6, 2013, pp. 2398-2408.
IEEE DOI 1307
atmospheric turbulence, wavelet transforms, Image quality BibRef

Anantrasirichai, N., Achim, A., Bull, D.R.,
Atmospheric Turbulence Mitigation for Sequences with Moving Objects Using Recursive Image Fusion,
ICIP18(2895-2899)
IEEE DOI 1809
Distortion, Image fusion, Atmospheric waves, Kalman filters, Image restoration, Atmospheric modeling, Heating systems, restoration BibRef

Mao, Y., Gilles, J.[Jérôme],
Non-rigid Geometric Distortions Correction: Application to atmospheric turbulence stabilization,
IPI(6), No. 3, August 2012, pp. 531-546.
DOI Link
See also Mao-Gilles Stabilization Algorithm. BibRef 1208

Gilles, J.[Jérôme], Dagobert, T.[Tristan], de Franchis, C.[Carlo],
Atmospheric Turbulence Restoration by Diffeomorphic Image Registration and Blind Deconvolution,
ACIVS08(xx-yy).
Springer DOI 0810
BibRef

Gilles, J.[Jérôme],
Mao-Gilles Stabilization Algorithm,
IPOL(2012), No. 2012, pp. xx-yy.
DOI Link 1309
Code, Stabilization.
See also Non-rigid Geometric Distortions Correction: Application to atmospheric turbulence stabilization. BibRef

Micheli, M.[Mario], Lou, Y.F.[Yi-Fei], Soatto, S.[Stefano], Bertozzi, A.L.[Andrea L.],
A Linear Systems Approach to Imaging Through Turbulence,
JMIV(48), No. 1, January 2014, pp. 185-201.
Springer DOI 1402
BibRef

Gibson, K.B., Nguyen, T.Q.,
An Analysis and Method for Contrast Enhancement Turbulence Mitigation,
IP(23), No. 7, July 2014, pp. 3179-3190.
IEEE DOI 1407
Atmospheric measurements BibRef

Héas, P., Lavancier, F., Kadri-Harouna, S.,
Self-Similar Prior and Wavelet Bases for Hidden Incompressible Turbulent Motion,
SIIMS(7), No. 2, 2014, pp. 1171-1209.
DOI Link 1407
BibRef

Toselli, I.[Italo],
Introducing the concept of anisotropy at different scales for modeling optical turbulence,
JOSA-A(31), No. 8, August 2014, pp. 1868-1875.
DOI Link 1408
Atmospheric and oceanic optics BibRef

Meinhardt-Llopis, E.[Enric], Micheli, M.[Mario],
Implementation of the Centroid Method for the Correction of Turbulence,
IPOL(2014), No. 1, pp. 187-195.
DOI Link 1408
Code, Turbulence.
See also Suppression of Atmospheric Turbulence in Video Using an Adaptive Control Grid Interpolation Approach.
See also Linear Systems Approach to Imaging Through Turbulence, A. BibRef

Gal, R.[Ronen], Kiryati, N.[Nahum], Sochen, N.[Nir],
Progress in the restoration of image sequences degraded by atmospheric turbulence,
PRL(48), No. 1, 2014, pp. 8-14.
Elsevier DOI 1410
Atmospheric turbulence BibRef

Paul, N.[Nicolas], de Chillaz, A.[Antoine], Collette, J.L.[Jean-Luc],
On-line restoration for turbulence degraded video in nuclear power plant reactors,
SIViP(9), No. 3, March 2015, pp. 601-610.
WWW Link. 1503
BibRef

Collins, R.[Richard], Triplett, C.[Colin], Barjatya, A.[Aroh], Lehmacher, G.[Gerald], Fritts, D.[David],
Using lidar and rockets to explore turbulence in the atmosphere,
SPIE(Newsroom), May 7, 2015.
DOI Link 1307
A lidar documents weather conditions in the upper atmosphere for rocket measurements of turbulence to yield benchmark measurements for atmospheric circulation models. BibRef

Liu, J.[Jony], Carhart, G.W.[Gary W.], Beresnev, L.A.[Leonid A.], McElhenny, J.[John], Jackson, C.[Christopher], Ejzak, G.[Garrett], Browning, T.[Tyler], Cayci, F.[Furkan], Kiamilev, F.[Fouad],
Real-time processing for long-range imaging,
SPIE(Newsroom), May 29, 2015.
DOI Link 1507
A hybrid system that incorporates advanced adaptive optics and algorithm acceleration techniques can compensate wavefront aberrations caused by turbulence and improve image quality. BibRef

Xie, Y., Zhang, W., Tao, D., Hu, W., Qu, Y., Wang, H.,
Removing Turbulence Effect via Hybrid Total Variation and Deformation-Guided Kernel Regression,
IP(25), No. 10, October 2016, pp. 4943-4958.
IEEE DOI 1610
atmospheric turbulence BibRef

Dijk, J.[Judith], Schutte, K.[Klamer], Nieuwenhuizen, R.[Robert],
Turbulence mitigation methods for sea scenario imaging,
SPIE(Newsroom), November 29, 2016.
DOI Link 1612
An adapted processing chain enhances targets of interest in camera images that have a non-static background, and can thus enable longer-range classification and identification of ships. BibRef

Gilles, J.[Jérôme], Ferrante, N.B.[Nicholas B.],
Open Turbulent Image Set (OTIS),
PRL(86), No. 1, 2017, pp. 38-41.
Elsevier DOI 1702
Turbulence BibRef

Zhang, C.[Chao], Zhou, F.[Fugen], Xue, B.[Bindang], Xue, W.F.[Wen-Fang],
Stabilization of atmospheric turbulence-distorted video containing moving objects using the monogenic signal,
SP:IC(63), 2018, pp. 19-29.
Elsevier DOI 1804
Atmospheric turbulence, Video stabilization, Monogenic signal BibRef

Ineichen, P.[Pierre],
High Turbidity Solis Clear Sky Model: Development and Validation,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Gilles, J., Alvarez, F., Ferrante, N., Fortman, M., Tahir, L., Tarter, A., von Seeger, A.,
Detection of moving objects through turbulent media. Decomposition of Oscillatory vs Non-Oscillatory spatio-temporal vector fields,
IVC(73), 2018, pp. 40-55.
Elsevier DOI 1805
Moving object detection, Atmospheric turbulence, Decomposition, Curvelet spaces BibRef

Dagobert, T.[Tristan], Tendero, Y.[Yohann], Landeau, S.[Stéphane],
Study of the Principal Component Analysis Method for the Correction of Images Degraded by Turbulence,
IPOL(8), 2018, pp. 388-407.
DOI Link 1812
Code, Turbulence.
See also Blur Identification Based on Kurtosis Minimization. BibRef

Nunes, P.[Prifiyia], Israni, D.[Dippal], Karthick, D., Shah, A.[Arpita],
A novel approach for mitigating atmospheric turbulence using weighted average Sobolev gradient and Laplacian,
IJCVR(9), No. 5, 2019, pp. 515-526.
DOI Link 1909
BibRef

Peña, A.[Alfredo], Mann, J.[Jakob],
Turbulence Measurements with Dual-Doppler Scanning Lidars,
RS(11), No. 20, 2019, pp. xx-yy.
DOI Link 1910
BibRef

Ono, Y.H.[Yoshito H.], Correia, C.[Carlos], Conan, R.[Rodolphe], Blanco, L.[Leonardo], Neichel, B.[Benoit], Fusco, T.[Thierry],
Fast iterative tomographic wavefront estimation with recursive Toeplitz reconstructor structure for large-scale systems,
JOSA-A(35), No. 8, August 2018, pp. 1330-1345.
DOI Link 1912
Active or adaptive optics, Inverse problems, Atmospheric turbulence, Computation methods, Wavefront aberrations BibRef

Li, Y.H.[Yin-Hao], Ogawa, K.[Katsuhisa], Iwamoto, Y.[Yutaro], Chen, Y.W.[Yen-Wei],
Novel Image Restoration Method Based on Multi-Frame Super-Resolution for Atmospherically Distorted Images,
IET-IPR(14), No. 1, January 2020, pp. 168-175.
DOI Link 1912
BibRef

Duan, M.[Meng], Xu, B.[Bing], Li, Z.W.[Zhi-Wei], Wu, W.H.[Wen-Hao], Cao, Y.M.[Yun-Meng], Liu, J.H.[Ji-Hong], Wang, G.[Guanya], Hou, J.X.[Jing-Xin],
A New Weighting Method by Considering the Physical Characteristics of Atmospheric Turbulence and Decorrelation Noise in SBAS-InSAR,
RS(12), No. 16, 2020, pp. xx-yy.
DOI Link 2008
BibRef

Deledalle, C.A.[Charles-Alban], Gilles, J.[Jérôme],
Blind atmospheric turbulence deconvolution,
IET-IPR(14), No. 14, December 2020, pp. 3422-3432.
DOI Link 2012
BibRef

Kim, J.H.[Jung-Hoon], Park, J.R.[Ja-Rin], Kim, S.H.[Soo-Hyun], Kim, J.[Jeonghoe], Lee, E.[Eunjeong], Baek, S.W.[Seung-Woo], Lee, G.[Gyuwon],
A Detection of Convectively Induced Turbulence Using in Situ Aircraft and Radar Spectral Width Data,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Patel, K.[Krina], Israni, D.[Dippal], Garg, D.[Dweepna],
An Efficient Local Block Sobolev Gradient and Laplacian Approach for Elimination of Atmospheric Turbulence,
IJIG(21), No. 4, October 2021 2021, pp. 2150043.
DOI Link 2110
BibRef

Hua, X.[Xia], Pan, C.[Chao], Shi, Y.[Yu], Liu, J.G.[Jian-Guo], Hong, H.Y.[Han-Yu],
Removing Atmospheric Turbulence Effects Via Geometric Distortion and Blur Representation,
GeoRS(60), 2022, pp. 1-13.
IEEE DOI 2112
Distortion, Image restoration, Strain, Optical distortion, Feature extraction, Image edge detection, Image reconstruction, nonrigid image registration BibRef

Lim, H.C.[Hyung-Chul], Choi, C.S.[Chul-Sung], Sung, K.P.[Ki-Pyoung], Park, J.U.[Jong-Uk], Choi, M.[Mansoo],
Centroid Error Analysis of Beacon Tracking under Atmospheric Turbulence for Optical Communication Links,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Chen, G.P.[Gong-Ping], Gao, Z.S.[Zhi-Sheng], Zhou, B.[Bin], Zuo, C.L.[Cheng-Lin],
Optimization and regularization of complex task decomposition for blind removal of multi-factor degradation,
JVCIR(82), 2022, pp. 103384.
Elsevier DOI 2201
Complex task, Decomposition regularization, Convolutional neural network, Atmospheric turbulence, Blind restoration BibRef

Chen, Z.[Ze], Tian, Y.F.[Yu-Fang], Lü, D.[Daren],
Turbulence Parameters in the Troposphere: Lower Stratosphere Observed by Beijing MST Radar,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Fazlali, H.[Hamidreza], Shirani, S.[Shahram], Bradford, M.[Michael], Kirubarajan, T.[Thia],
Atmospheric Turbulence Removal in Long-Range Imaging Using a Data-Driven-Based Approach,
IJCV(130), No. 1, January 2022, pp. 1031-1049.
Springer DOI 2204
BibRef

Rai, S.N.[Shyam Nandan], Jawahar, C.V.,
Removing Atmospheric Turbulence via Deep Adversarial Learning,
IP(31), 2022, pp. 2633-2646.
IEEE DOI 2204
Image restoration, Atmospheric modeling, Nonlinear distortion, Deep learning, Task analysis, Noise reduction, generative adversarial networks BibRef

Bi, C.C.[Cui-Cui], Qing, C.[Chun], Wu, P.F.[Peng-Fei], Jin, X.M.[Xiao-Mei], Liu, Q.[Qing], Qian, X.[Xianmei], Zhu, W.Y.[Wen-Yue], Weng, N.Q.[Ning-Quan],
Optical Turbulence Profile in Marine Environment with Artificial Neural Network Model,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Xu, M.M.[Man-Man], Shao, S.Y.[Shi-Yong], Weng, N.Q.[Ning-Quan], Liu, Q.[Qing],
Analysis of the Optical Turbulence Model Using Meteorological Data,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Xu, M.M.[Man-Man], Shao, S.Y.[Shi-Yong], Weng, N.Q.[Ning-Quan], Liu, Q.[Qing],
Analysis of Optical Turbulence over the South China Sea Using Balloon-Borne Microthermal Data and ERA5 Data,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Chan, S.H.[Stanley H.],
Tilt-Then-Blur or Blur-Then-Tilt? Clarifying the Atmospheric Turbulence Model,
SPLetters(29), 2022, pp. 1833-1837.
IEEE DOI 2209
Atmospheric modeling, Image restoration, Mathematical models, Phase distortion, Computational modeling, Refractive index, signal processing BibRef

Shu, J.[Jie], Xie, C.Z.[Chun-Zhi], Gao, Z.S.[Zhi-Sheng],
Blind Restoration of Atmospheric Turbulence-Degraded Images Based on Curriculum Learning,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Su, C.D.[Chang-Dong], Wu, X.Q.[Xiao-Qing], Guo, Y.M.[Yi-Ming], Zhang, S.[Shitai], Wang, Z.Y.[Zhi-Yuan], Shi, D.F.[Dong-Feng],
Atmospheric turbulence degraded image restoration using a modified dilated convolutional network,
IET-IPR(16), No. 13, 2022, pp. 3507-3517.
DOI Link 2210
BibRef

Peña, A.[Alfredo], Mann, J.[Jakob], Angelou, N.[Nikolas], Jacobsen, A.[Arnhild],
A Motion-Correction Method for Turbulence Estimates from Floating Lidars,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Teng, Y.P.[Yu-Peng], Li, T.Y.[Tian-Yan], Ma, S.Q.[Shu-Qing], Chen, H.B.[Hong-Bin],
Turbulence: A Significant Role in Clear-Air Echoes of CINRAD/SA at Night,
RS(15), No. 7, 2023, pp. 1781.
DOI Link 2304
BibRef

Anantrasirichai, N.[Nantheera],
Atmospheric turbulence removal with complex-valued convolutional neural network,
PRL(171), 2023, pp. 69-75.
Elsevier DOI 2306
Image restoration, Deep learning, Complex-valued convolutional neural network, Atmospheric turbulence BibRef

Abdukirim, A.[Azezigul], Ren, Y.[Yichong], Tao, Z.W.[Zhi-Wei], Liu, S.[Shiwei], Li, Y.L.[Yan-Ling], Deng, H.[Hanling], Rao, R.Z.[Rui-Zhong],
Effects of Atmospheric Coherent Time on Inverse Synthetic Aperture Ladar Imaging through Atmospheric Turbulence,
RS(15), No. 11, 2023, pp. 2883.
DOI Link 2306
BibRef

Zhou, X.X.[Xing-Xu], Zhang, C.[Chao], Li, Y.Y.[Yun-Ying], Zhang, Z.W.[Zhi-Wei],
Comparison of Spring Wind Gusts in the Eastern Part of the Tibetan Plateau and along the Coast: The Role of Turbulence,
RS(15), No. 14, 2023, pp. 3655.
DOI Link 2307
BibRef

Guo, Y.M.[Yi-Ming], Wu, X.Q.[Xiao-Qing], Qing, C.[Chun], Liu, L.Y.[Li-Yong], Yang, Q.[Qike], Hu, X.D.[Xiao-Dan], Qian, X.M.[Xian-Mei], Shao, S.Y.[Shi-Yong],
Blind Restoration of a Single Real Turbulence-Degraded Image Based on Self-Supervised Learning,
RS(15), No. 16, 2023, pp. 4076.
DOI Link 2309
BibRef

Li, X.X.[Xiang-Xi], Liu, X.[Xingling], Wei, W.L.[Wei-Long], Zhong, X.[Xing], Ma, H.T.[Hao-Tong], Chu, J.Q.[Jun-Qiu],
A DeturNet-Based Method for Recovering Images Degraded by Atmospheric Turbulence,
RS(15), No. 20, 2023, pp. 5071.
DOI Link 2310
BibRef

Liu, X.Q.[Xiang-Qing], Li, G.[Gang], Zhao, Z.Y.[Zhen-Yang], Cao, Q.[Qi], Zhang, Z.J.[Zi-Jun], Yan, S.[Shaoan], Xie, J.B.[Jian-Bin], Tang, M.H.[Ming-Hua],
EAF-WGAN: Enhanced Alignment Fusion-Wasserstein Generative Adversarial Network for Turbulent Image Restoration,
CirSysVideo(33), No. 10, October 2023, pp. 5605-5616.
IEEE DOI 2310
BibRef

Chan, S.H.[Stanley H.], Chimitt, N.[Nicholas],
Computational Imaging Through Atmospheric Turbulence,
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ICIP23(3568-3572)
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NeRT: Implicit Neural Representations for Unsupervised Atmospheric Turbulence Mitigation,
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ICIP22(3386-3390)
IEEE DOI 2211
Training, Image quality, Codes, Image recognition, Atmospheric modeling, Face recognition, Imaging, deblurring BibRef

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ICIP22(2051-2055)
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Technological innovation, Convolution, Statistical analysis, Numerical analysis, Atmospheric modeling, Imaging, Training data, Low-level and physics-based vision BibRef

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Nair, N.G.[Nithin Gopalakrishnan], Patel, V.M.[Vishal M.],
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WACV18(512-520)
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ICIVC17(423-427)
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Correlation, Discrete cosine transforms, Distortion measurement, Image restoration, Wavelet transforms, deblurring efficiency, image ambiguity, image distortion, local kurtosis, wavelet, transform BibRef

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A Centroid Algorithm for Stabilization of Turbulence-Degraded Underwater Videos,
DICTA16(1-6)
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Image reconstruction BibRef

Kamenetsky, D.[Dmitri], Zucchi, M.[Michael], Nichols, G.[Geoff], Booth, D.[David], Lambert, A.[Andrew],
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Australia BibRef

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Atmospheric Turbulence Mitigation Using Optical Flow,
ICPR14(883-888)
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Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Super Resolution for Remote Sensing Applications .