15.2.12.10 Destriping Images, Pushbroom, Scanner, Remote Sensing Imagry

Chapter Contents (Back)
Destriping. Radiometric Calibration. See also Pushbroom Camera Calibration Issues.

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

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., Yan, L., Zhong, S.,
Hyper-Laplacian Regularized Unidirectional Low-Rank Tensor Recovery for Multispectral Image Denoising,
CVPR17(5901-5909)
IEEE DOI 1711
Analytical models, Computational modeling, Correlation, Noise reduction, Optimization, Tensile stress, Visualization BibRef

Chang, Y., Yan, L., Zhong, S.,
Transformed Low-Rank Model for Line Pattern Noise Removal,
ICCV17(1735-1743)
IEEE DOI 1802
geophysical image processing, image denoising, image resolution, random noise, remote sensing, 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.[Yushi], 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.[Mingchang], 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


Li, Y., Zhang, B., Florent, R.,
Fast de-streaking method using plain neural network,
ICIP17(1886-1889)
IEEE DOI 1803
Biological neural networks, Computer vision, 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 .


Last update:Sep 28, 2020 at 12:04:43