Horn, B.K.P.[Berthold K.P.], and
Woodham, R.J.[Robert J.],
Destriping Satellite Images,
CGIP(10), No. 1, May 1979, pp. 69-83.
Elsevier DOI
BibRef
7905
Earlier:
MIT AI Memo-467, March 1978
BibRef
Corsini, G.,
Diani, M.,
Walzel, T.,
Striping Removal in MOS-B Data,
GeoRS(38), No. 3, May 2000, pp. 1439-1446.
IEEE Top Reference.
0006
BibRef
Schlapfer, D.,
Nieke, J.,
Itten, K.I.,
Spatial PSF Nonuniformity Effects in Airborne Pushbroom Imaging
Spectrometry Data,
GeoRS(45), No. 2, February 2007, pp. 458-468.
IEEE DOI
0703
BibRef
Manikandan, S.,
Ebenezer, D.,
Nonlinear Decision-Based Algorithm for Removal of Strip Lines, Drop
Lines, Blotches, Band Missing and Impulses in Images and Videos,
JIVP(2008), No. 2008, pp. xx-yy.
DOI Link
0811
BibRef
di Bisceglie, M.,
Episcopo, R.,
Galdi, C.,
Ullo, S.L.,
Destriping MODIS Data Using Overlapping Field-of-View Method,
GeoRS(47), No. 2, February 2009, pp. 637-651.
IEEE DOI
0903
BibRef
Shen, H.,
Zhang, L.,
A MAP-Based Algorithm for Destriping and Inpainting of Remotely Sensed
Images,
GeoRS(47), No. 5, May 2009, pp. 1492-1502.
IEEE DOI
0904
BibRef
Bouali, M.,
Ladjal, S.,
Toward Optimal Destriping of MODIS Data Using a Unidirectional
Variational Model,
GeoRS(49), No. 8, August 2011, pp. 2924-2935.
IEEE DOI
1108
BibRef
Pande-Chhetri, R.[Roshan],
Abd-Elrahman, A.[Amr],
De-striping hyperspectral imagery using wavelet transform and adaptive
frequency domain filtering,
PandRS(66), No. 5, September 2011, pp. 620-636.
Elsevier DOI
1110
De-striping; Wavelet decomposition analysis; Fourier transform;
Hyperspectral; De-noising
BibRef
Tsai, F.,
Chen, W.W.,
Striping Noise Detection and Correction of Remote Sensing Images,
GeoRS(46), No. 12, December 2008, pp. 4122-4131.
IEEE DOI
0812
BibRef
Lu, X.Q.[Xiao-Qiang],
Wang, Y.L.[Yu-Long],
Yuan, Y.[Yuan],
Graph-Regularized Low-Rank Representation for Destriping of
Hyperspectral Images,
GeoRS(51), No. 7, 2013, pp. 4009-4018.
IEEE DOI
1307
Destriping; graph regularizer; hyperspectral image
See also Substance Dependence Constrained Sparse NMF for Hyperspectral Unmixing.
BibRef
Yuan, Y.[Yuan],
Zheng, X.,
Lu, X.Q.[Xiao-Qiang],
Discovering Diverse Subset for Unsupervised Hyperspectral Band
Selection,
IP(26), No. 1, January 2017, pp. 51-64.
IEEE DOI
1612
feature selection
BibRef
Yuan, Y.[Yuan],
Zheng, X.,
Lu, X.Q.[Xiao-Qiang],
Spectral-Spatial Kernel Regularized for Hyperspectral Image Denoising,
GeoRS(53), No. 7, July 2015, pp. 3815-3832.
IEEE DOI
1503
Computational modeling
BibRef
Bouali, M.,
Ignatov, A.,
Estimation of Detector Biases in MODIS Thermal Emissive Bands,
GeoRS(51), No. 7, 2013, pp. 4339-4348.
IEEE DOI
1307
Ocean temperature;
Moderate Resolution Imaging Spectroradiometer (MODIS);
striping
BibRef
Rogass, C.[Christian],
Mielke, C.[Christian],
Scheffler, D.[Daniel],
Boesche, N.K.[Nina K.],
Lausch, A.[Angela],
Lubitz, C.[Christin],
Brell, M.[Maximilian],
Spengler, D.[Daniel],
Eisele, A.[Andreas],
Segl, K.[Karl],
Guanter, L.[Luis],
Reduction of Uncorrelated Striping Noise: Applications for
Hyperspectral Pushbroom Acquisitions,
RS(6), No. 11, 2014, pp. 11082-11106.
DOI Link
1412
BibRef
Schlapfer, D.,
Richter, R.,
Feingersh, T.,
Operational BRDF Effects Correction for Wide-Field-of-View Optical
Scanners (BREFCOR),
GeoRS(53), No. 4, April 2015, pp. 1855-1864.
IEEE DOI
1502
Bidirectional Reflectance Distribution Function (BDRF).
calibration
BibRef
Chang, Y.,
Yan, L.,
Fang, H.,
Luo, C.,
Anisotropic Spectral-Spatial Total Variation Model for Multispectral
Remote Sensing Image Destriping,
IP(24), No. 6, June 2015, pp. 1852-1866.
IEEE DOI
1504
Detectors
BibRef
Kim, D.C.[Dae-Chul],
Kyung, W.J.[Wang-Jun],
Ha, H.G.[Ho-Gun],
Ha, Y.H.[Yeong-Ho],
Moiré Reduction Using Inflection Point and Color Variation in Digital
Camera of No Optical Low Pass Filter,
IEICE(E98-D), No. 12, December 2015, pp. 2290-2298.
WWW Link.
1601
Not stripes, but...
Optical low pass filter generally used in digital camera, without it the
Moiré pattern is an issue.
BibRef
Liu, X.,
Lu, X.,
Shen, H.F.[Huan-Feng],
Yuan, Q.Q.[Qiang-Qiang],
Jiao, Y.,
Zhang, L.P.[Liang-Pei],
Stripe Noise Separation and Removal in Remote Sensing Images by
Consideration of the Global Sparsity and Local Variational Properties,
GeoRS(54), No. 5, May 2016, pp. 3049-3060.
IEEE DOI
1604
geophysical image processing
See also Multiframe Super-Resolution Employing a Spatially Weighted Total Variation Model.
BibRef
Chang, Y.[Yi],
Yan, L.X.[Lu-Xin],
Wu, T.[Tao],
Zhong, S.[Sheng],
Remote Sensing Image Stripe Noise Removal:
From Image Decomposition Perspective,
GeoRS(54), No. 12, December 2016, pp. 7018-7031.
IEEE DOI
1612
geophysical image processing
BibRef
Chang, Y.[Yi],
Yan, L.X.[Lu-Xin],
Zhao, X.L.[Xi-Le],
Fang, H.Z.[Hou-Zhang],
Zhang, Z.J.[Zhi-Jun],
Zhong, S.[Sheng],
Weighted Low-Rank Tensor Recovery for Hyperspectral Image Restoration,
Cyber(50), No. 11, November 2020, pp. 4558-4572.
IEEE DOI
2011
Image restoration, Tensors, Task analysis, Correlation,
Noise reduction, Sparse matrices,
low-rank tensor approximation (LRTA)
See also Double-Factor-Regularized Low-Rank Tensor Factorization for Mixed Noise Removal in Hyperspectral Image.
BibRef
Chang, Y.[Yi],
Yan, L.X.[Lu-Xin],
Chen, B.L.[Bing-Ling],
Zhong, S.[Sheng],
Tian, Y.H.[Yong-Hong],
Hyperspectral Image Restoration: Where Does the Low-Rank Property
Exist,
GeoRS(59), No. 8, August 2021, pp. 6869-6884.
IEEE DOI
2108
Tensile stress, Image restoration, Task analysis, Noise reduction,
Correlation, Sparse matrices, Hyperspectral imaging,
low-rank tensor recovery
BibRef
Su, Y.C.[Yan-Chi],
Zhu, H.R.[Hao-Ran],
Wong, K.C.[Ka-Chun],
Chang, Y.[Yi],
Li, X.T.[Xiang-Tao],
Hyperspectral Image Denoising via Weighted Multidirectional Low-Rank
Tensor Recovery,
Cyber(53), No. 5, May 2023, pp. 2753-2766.
IEEE DOI
2305
Tensors, Noise reduction, Correlation, Hyperspectral imaging,
Computational modeling, TV, Optimization,
mixed noise
BibRef
Chang, Y.[Yi],
Yan, L.X.[Lu-Xin],
Zhong, S.,
Hyper-Laplacian Regularized Unidirectional Low-Rank Tensor Recovery
for Multispectral Image Denoising,
CVPR17(5901-5909)
IEEE DOI
1711
BibRef
And:
Transformed Low-Rank Model for Line Pattern Noise Removal,
ICCV17(1735-1743)
IEEE DOI
1802
Analytical models, Computational modeling, Correlation,
Noise reduction, Optimization, Tensile stress, Visualization.
geophysical image processing, image denoising, image resolution,
random noise, remote sensing
BibRef
Cao, Y.,
Yang, M.Y.,
Tisse, C.L.,
Effective Strip Noise Removal for Low-Textured Infrared Images Based
on 1-D Guided Filtering,
CirSysVideo(26), No. 12, December 2016, pp. 2176-2188.
IEEE DOI
1612
Histograms
BibRef
Chen, Y.[Yong],
Huang, T.Z.[Ting-Zhu],
Zhao, X.L.[Xi-Le],
Deng, L.J.[Liang-Jian],
Huang, J.[Jie],
Stripe noise removal of remote sensing images by total variation
regularization and group sparsity constraint,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link
1706
BibRef
Dou, H.X.[Hong-Xia],
Huang, T.Z.[Ting-Zhu],
Deng, L.J.[Liang-Jian],
Zhao, X.L.[Xi-Le],
Huang, J.[Jie],
Directional L_0 Sparse Modeling for Image Stripe Noise Removal,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link
1804
BibRef
Dou, H.X.[Hong-Xia],
Huang, T.Z.[Ting-Zhu],
Deng, L.J.[Liang-Jian],
Chen, Y.[Yong],
Stripe noise removal of remote sensing image with a directional L_0
sparse model,
ICIP17(3505-3509)
IEEE DOI
1803
Closed-form solutions, Convergence, Mathematical model,
Minimization, Remote sensing, Superluminescent diodes, Visualization
BibRef
Gao, G.,
Gu, Y.,
Multitemporal Landsat Missing Data Recovery Based on Tempo-Spectral
Angle Model,
GeoRS(55), No. 7, July 2017, pp. 3656-3668.
IEEE DOI
1706
Clouds, Earth, Extraterrestrial measurements, Remote sensing,
Satellites, Sensors, Usability, Landsat, missing data,
multitemporal images, similarity replacement, tempo-spectral,
angle, mapping, (TSAM)
BibRef
Malik, P.[Parveen],
Karthik, K.[Kannan],
Iterative content adaptable purple fringe detection,
SIViP(12), No. 1, January 2018, pp. 181-188.
Springer DOI
1801
Not stripes, other defects.
Defects in the sensor grid induce fringing artifacts
near high-contrast regions.
BibRef
Liu, X.,
Shen, H.,
Yuan, Q.,
Lu, X.,
Zhou, C.,
A Universal Destriping Framework Combining 1-D and 2-D Variational
Optimization Methods,
GeoRS(56), No. 2, February 2018, pp. 808-822.
IEEE DOI
1802
image denoising, iterative methods, least squares approximations,
optimisation, remote sensing,
variational optimization
BibRef
Yanovsky, I.[Igor],
Dragomiretskiy, K.[Konstantin],
Variational Destriping in Remote Sensing Imagery:
Total Variation with L1 Fidelity,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link
1804
BibRef
Teng, Y.[Yidan],
Zhang, Y.[Ye],
Ti, C.L.[Chun-Li],
Zhang, J.P.[Jun-Ping],
Hyperspectral Image Resolution Enhancement Approach Based on Local
Adaptive Sparse Unmixing and Subpixel Calibration,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link
1805
BibRef
Teng, Y.[Yidan],
Zhang, Y.[Ye],
Chen, Y.S.[Yu-Shi],
Ti, C.L.[Chun-Li],
A Novel Hyperspectral Images Destriping Method Based on Edge
Reconstruction and Adaptive Morphological Operators,
ICIP14(2948-2952)
IEEE DOI
1502
Algorithm design and analysis
BibRef
Song, Q.[Qiong],
Wang, Y.H.[Yue-Huan],
Yan, X.Y.[Xiao-Yun],
Gu, H.[Haiguo],
Remote Sensing Images Stripe Noise Removal by Double Sparse
Regulation and Region Separation,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link
1808
BibRef
Zhou, B.[Bo],
Luo, Y.[Yin],
Chen, B.G.[Bao-Guo],
Wang, M.C.[Ming-Chang],
Peng, L.[Li],
Liang, K.[Kun],
Local spatial correlation-based stripe non-uniformity correction
algorithm for single infrared images,
SP:IC(72), 2019, pp. 47-57.
Elsevier DOI
1902
Infrared imaging, Stripe noise, Non-uniformity correction,
De-striping, Spatial correlation
BibRef
Sun, Y.J.[Yun-Jia],
Huang, T.Z.[Ting-Zhu],
Ma, T.H.[Tian-Hui],
Chen, Y.[Yong],
Remote Sensing Image Stripe Detecting and Destriping Using the Joint
Sparsity Constraint with Iterative Support Detection,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link
1903
BibRef
Li, Q.Y.[Qing-Yang],
Zhong, R.F.[Ruo-Fei],
Wang, Y.[Ya],
A Method for the Destriping of an Orbita Hyperspectral Image with
Adaptive Moment Matching and Unidirectional Total Variation,
RS(11), No. 18, 2019, pp. xx-yy.
DOI Link
1909
BibRef
He, L.X.[Lu-Xiao],
Wang, M.[Mi],
Chang, X.[Xueli],
Zhang, Z.Q.[Zhi-Qi],
Feng, X.X.[Xiao-Xiao],
Removal of Large-Scale Stripes Via Unidirectional Multiscale
Decomposition,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link
1911
BibRef
Liu, N.,
Li, W.,
Tao, R.,
Fowler, J.E.,
Wavelet-Domain Low-Rank/Group-Sparse Destriping for Hyperspectral
Imagery,
GeoRS(57), No. 12, December 2019, pp. 10310-10321.
IEEE DOI
1912
Hyperspectral imaging, Discrete wavelet transforms,
Image decomposition, Detectors, Destriping, group sparsity,
wavelet transform
BibRef
Liu, L.,
Xu, L.,
Fang, H.,
Simultaneous Intensity Bias Estimation and Stripe Noise Removal in
Infrared Images Using the Global and Local Sparsity Constraints,
GeoRS(58), No. 3, March 2020, pp. 1777-1789.
IEEE DOI
2003
Destriping, infrared (IR) imaging, intensity bias correction,
optimization-based model, sparsity
BibRef
Kong, X.Y.[Xiang-Yang],
Zhao, Y.Q.[Yong-Qiang],
Xue, J.[Jize],
Chan, J.C.W.[Jonathan Cheung-Wai],
Kong, S.G.[Seong G.],
Global and Local Tensor Sparse Approximation Models for Hyperspectral
Image Destriping,
RS(12), No. 4, 2020, pp. xx-yy.
DOI Link
2003
BibRef
Cui, H.,
Jia, P.,
Zhang, G.,
Jiang, Y.,
Li, L.,
Wang, J.,
Hao, X.,
Multiscale Intensity Propagation to Remove Multiplicative Stripe
Noise From Remote Sensing Images,
GeoRS(58), No. 4, April 2020, pp. 2308-2323.
IEEE DOI
2004
Destriping, hyperspectral remote sensing image,
multiplicative noise, radiometric normalization
BibRef
Chang, Y.,
Chen, M.,
Yan, L.,
Zhao, X.,
Li, Y.,
Zhong, S.,
Toward Universal Stripe Removal via Wavelet-Based Deep Convolutional
Neural Network,
GeoRS(58), No. 4, April 2020, pp. 2880-2897.
IEEE DOI
2004
Convolutional neural network (CNN), destriping, image decomposition, wavelet
BibRef
Huang, Z.,
Zhang, Y.,
Li, Q.,
Li, X.,
Zhang, T.,
Sang, N.,
Hong, H.,
Joint Analysis and Weighted Synthesis Sparsity Priors for
Simultaneous Denoising and Destriping Optical Remote Sensing Images,
GeoRS(58), No. 10, October 2020, pp. 6958-6982.
IEEE DOI
2009
Noise reduction, Optical imaging, Optical sensors, Remote sensing,
Dictionaries, Optical noise, MODIS,
weighted synthesis sparse representation (SSR) (WSSR)
BibRef
Tu, Z.Z.[Zheng-Zhong],
Lin, J.[Jessie],
Wang, Y.L.[Yi-Lin],
Adsumilli, B.[Balu],
Bovik, A.C.[Alan C.],
Adaptive Debanding Filter,
SPLetters(27), 2020, pp. 1715-1719.
IEEE DOI
2010
Quantization (signal), Streaming media, Smoothing methods,
Image edge detection, Image reconstruction, Visualization,
post-processing
BibRef
Zeng, Q.J.[Qing-Jie],
Qin, H.L.[Han-Lin],
Yan, X.[Xiang],
Yang, T.W.[Ting-Wu],
Fourier Domain Anomaly Detection and Spectral Fusion for Stripe Noise
Removal of TIR Imagery,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link
2011
BibRef
Yang, F.[Fang],
Chen, X.[Xin],
Chai, L.[Li],
Hyperspectral Image Destriping and Denoising Using Stripe and
Spectral Low-Rank Matrix Recovery and Global Spatial-Spectral Total
Variation,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link
2103
BibRef
Wang, Q.M.[Qun-Ming],
Wang, L.X.[Lan-Xing],
Li, Z.B.[Zhong-Bin],
Tong, X.H.[Xiao-Hua],
Atkinson, P.M.[Peter M.],
Spatial-Spectral Radial Basis Function-Based Interpolation for
Landsat ETM+ SLC-Off Image Gap Filling,
GeoRS(59), No. 9, September 2021, pp. 7901-7917.
IEEE DOI
2109
Remote sensing, Earth, Artificial satellites, Interpolation,
Satellite broadcasting, Reactive power, Histograms, Gap filling,
scan-line corrector (SLC)-off
BibRef
Zhao, S.H.[Shu-Heng],
Yuan, Q.Q.[Qiang-Qiang],
Li, J.[Jie],
Hu, Y.Z.[Yun-Ze],
Liu, X.X.[Xin-Xin],
Zhang, L.P.[Liang-Pei],
A Fast and Effective Irregular Stripe Removal Method for Moon
Mineralogy Mapper (M3),
GeoRS(60), 2022, pp. 1-19.
IEEE DOI
2112
Moon, Hyperspectral imaging, Correlation, Optimization,
Image restoration, Training, Technological innovation,
Moon mineralogy mapper (M³)
BibRef
Wu, X.B.[Xia-Bin],
Qu, H.S.[Hong-Song],
Zheng, L.L.[Liang-Liang],
Gao, T.[Tan],
Zhang, Z.Y.[Zi-Yu],
A Remote Sensing Image Destriping Model Based on Low-Rank and
Directional Sparse Constraint,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Wang, C.J.[Cheng-Jun],
Xu, M.Z.[Miao-Zhong],
Jiang, Y.H.[Yong-Hua],
Zhang, G.[Guo],
Cui, H.[Hao],
Deng, G.[Guohui],
Lu, Z.Y.[Zhong-Yuan],
Toward Real Hyperspectral Image Stripe Removal via Direction
Constraint Hierarchical Feature Cascade Networks,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Li, B.B.[Bin-Bo],
Zhou, Y.[Ying],
Xie, D.H.[Dong-Hai],
Zheng, L.J.[Li-Juan],
Wu, Y.[Yu],
Yue, J.B.[Jia-Bao],
Jiang, S.W.[Shao-Wei],
Stripe Noise Detection of High-Resolution Remote Sensing Images Using
Deep Learning Method,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link
2202
BibRef
Li, J.[Jia],
Zeng, D.[Dan],
Zhang, J.J.[Jun-Jie],
Han, J.G.[Jun-Gong],
Mei, T.[Tao],
Column-Spatial Correction Network for Remote Sensing Image Destriping,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link
2208
BibRef
Zhang, D.G.[De-Gang],
Cheng, B.[Bo],
Shi, L.[Lu],
Gao, J.[Jie],
Long, T.F.[Teng-Fei],
Chen, B.[Bo],
Wang, G.Z.[Gui-Zhou],
A Destriping Algorithm for SDGSAT-1 Nighttime Light Images Based on
Anomaly Detection and Spectral Similarity Restoration,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link
2212
BibRef
Song, L.F.[Ling-Fei],
Huang, H.[Hua],
Simultaneous Destriping and Image Denoising Using a Nonparametric
Model With the EM Algorithm,
IP(32), 2023, pp. 1065-1077.
IEEE DOI
2302
Noise reduction, Maximum likelihood estimation, Image denoising,
Approximation algorithms, Signal processing algorithms,
conditional expectation
BibRef
Mao, J.L.[Jia-Li],
Qin, Z.K.[Zheng-Kun],
Li, J.[Juan],
Liu, G.Q.[Gui-Qing],
Huang, J.[Jing],
Comparative Analysis of Striping Noise between FY-3E MWTS-3 and FY-3D
MWTS-2,
RS(15), No. 5, 2023, pp. xx-yy.
DOI Link
2303
BibRef
Pan, E.[Erting],
Ma, Y.[Yong],
Mei, X.G.[Xiao-Guang],
Huang, J.[Jun],
Chen, Q.H.[Qi-Hai],
Ma, J.Y.[Jia-Yi],
Hyperspectral image destriping and denoising from a task
decomposition view,
PR(144), 2023, pp. 109832.
Elsevier DOI
2310
Image restoration, Hyperspectral images, Denoising,
Destriping, Multi-task learning
BibRef
Wu, X.B.[Xia-Bin],
Zheng, L.L.[Liang-Liang],
Liu, C.Y.[Chun-Yu],
Gao, T.[Tan],
Zhang, Z.Y.[Zi-Yu],
Yang, B.[Biao],
Single-Image Simultaneous Destriping and Denoising: Double Low-Rank
Property,
RS(15), No. 24, 2023, pp. 5710.
DOI Link
2401
BibRef
Li, B.[Bohan],
Zhang, Y.[Yong],
Chen, W.[Weicong],
Ma, Y.Z.[Yi-Zhe],
Li, L.[Linhan],
Neural Network-Based Investigation of Periodic Noise Reduction
Methods for High-Resolution Infrared Line Scanning Images,
RS(16), No. 5, 2024, pp. 841.
DOI Link
2403
BibRef
Chen, Z.J.[Zi-Jian],
Sun, W.[Wei],
Jia, J.[Jun],
Lu, F.F.[Fang-Fang],
Zhang, Z.C.[Zi-Cheng],
Liu, J.[Jing],
Huang, R.[Ru],
Min, X.K.[Xiong-Kuo],
Zhai, G.T.[Guang-Tao],
BAND-2k: Banding Artifact Noticeable Database for Banding Detection
and Quality Assessment,
CirSysVideo(34), No. 7, July 2024, pp. 6347-6362.
IEEE DOI Code:
WWW Link.
2407
Databases, Distortion, Quality assessment, Quantization (signal),
Quality of experience, Image edge detection, Image coding,
deep learning
BibRef
Huang, L.[Liang],
Gao, M.Y.[Ming-Yang],
Yuan, H.[Hangfei],
Li, M.X.[Ming-Xuan],
Nie, T.[Ting],
Stripe Noise Removal Algorithm for Infrared Remote Sensing Images
Based on Adaptive Weighted Variable Order Model,
RS(16), No. 17, 2024, pp. 3189.
DOI Link
2409
BibRef
Zhang, Z.L.[Ze-Lin],
Li, H.[Hua],
Du, Y.M.[Yong-Ming],
Chen, Y.[Yao],
Zhao, G.X.[Guo-Xiang],
Bian, Z.J.[Zun-Jian],
Cao, B.[Biao],
Xiao, Q.[Qing],
Liu, Q.H.[Qin-Huo],
Stripe Noise Elimination with a Novel Trend Repair Method for
Push-Broom Thermal Images,
RS(16), No. 17, 2024, pp. 3299.
DOI Link
2409
BibRef
Slocum, B.[Brittney],
Ladner, S.[Sherwin],
Lawson, A.[Adam],
Lewis, M.D.[Mark David],
McCarthy, S.[Sean],
Methodology for Removing Striping Artifacts Encountered in Planet
SuperDove Ocean-Color Products,
RS(16), No. 24, 2024, pp. 4707.
DOI Link
2501
BibRef
Zhang, H.[He],
Qian, W.X.[Wei-Xian],
Xu, Y.H.[Ying-Hui],
Zhang, K.[Kaimin],
Kong, X.F.[Xiao-Fang],
Wan, M.J.[Min-Jie],
Structural-information-awareness-based regularization model for
infrared image stripe noise removal,
JOSA-A(41), No. 9, September 2024, pp. 1723-1737.
DOI Link
2503
Deep learning, Imaging systems, Imaging techniques,
Infrared detectors, Infrared imaging, Spatial filtering
BibRef
Li, Y.,
Zhang, B.,
Florent, R.,
Fast de-streaking method using plain neural network,
ICIP17(1886-1889)
IEEE DOI
1803
Biological neural networks,
Image reconstruction, Radon, Training, Transforms, Neural network,
Streak reduction
BibRef
Gao, H.T.[Hui-Ting],
Liu, W.[Wei],
He, H.Y.[Hong-Yan],
Zhang, B.X.[Bing-Xian],
Jiang, C.[Cheng],
De-striping For Tdiccd Remote Sensing Image Based On Statistical
Features Of Histogram,
ISPRS16(B1: 311-316).
DOI Link
1610
BibRef
Yan, W.Y.[Wai Yeung],
Shaker, A.[Ahmed],
Reduction Of Striping Noise In Overlapping Lidar Intensity Data By
Radiometric Normalization,
ISPRS16(B1: 151-156).
DOI Link
1610
BibRef
Liu, H.[Hai],
Zhang, Z.L.[Zhao-Li],
Liu, S.[Sanya],
Liu, T.T.[Ting-Ting],
Chang, Y.[Yi],
Destriping algorithm with L0 sparsity prior for remote sensing images,
ICIP15(2295-2299)
IEEE DOI
1512
De-noise; Destriping; L0 norm; Regularization; Remote sensing image
BibRef
Chang, Y.[Yi],
Fang, H.Z.[Hou-Zhang],
Yan, L.[Luxin],
Liu, H.[Hai],
Joint blind deblurring and destriping for remote sensing images,
ICIP13(469-473)
IEEE DOI
1402
Hafnium
BibRef
Shen, H.F.[Huan-Feng],
Ai, T.H.[Ting-Hua],
Li, P.X.[Ping-Xiang],
Destriping and Inpainting of Remote Sensing Images Using Maximum
A-Posteriori Method,
ISPRS08(B1: 63 ff).
PDF File.
0807
BibRef
Choi, E.[Euncheol],
Kang, M.G.[Moon Gi],
Striping Noise Removal of Satellite Images by Nonlinear Mapping,
ICIAR06(II: 722-729).
Springer DOI
0610
BibRef
Chapter on Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following continues in
Vignetting Correction, Vignetting Analysis .