{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T12:40:13Z","timestamp":1782218413586,"version":"3.54.5"},"reference-count":46,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2018,2,26]],"date-time":"2018-02-26T00:00:00Z","timestamp":1519603200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Remote sensing images are often polluted by stripe noise, which leads to negative impact on visual performance. Thus, it is necessary to remove stripe noise for the subsequent applications, e.g., classification and target recognition. This paper commits to remove the stripe noise to enhance the visual quality of images, while preserving image details of stripe-free regions. Instead of solving the underlying image by variety of algorithms, we first estimate the stripe noise from the degraded images, then compute the final destriping image by the difference of the known stripe image and the estimated stripe noise. In this paper, we propose a non-convex     \u2113 0     sparse model for remote sensing image destriping by taking full consideration of the intrinsically directional and structural priors of stripe noise, and the locally continuous property of the underlying image as well. Moreover, the proposed non-convex model is solved by a proximal alternating direction method of multipliers (PADMM) based algorithm. In addition, we also give the corresponding theoretical analysis of the proposed algorithm. Extensive experimental results on simulated and real data demonstrate that the proposed method outperforms recent competitive destriping methods, both visually and quantitatively.<\/jats:p>","DOI":"10.3390\/rs10030361","type":"journal-article","created":{"date-parts":[[2018,2,27]],"date-time":"2018-02-27T03:36:12Z","timestamp":1519702572000},"page":"361","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":39,"title":["Directional \u21130 Sparse Modeling for Image Stripe Noise Removal"],"prefix":"10.3390","volume":"10","author":[{"given":"Hong-Xia","family":"Dou","sequence":"first","affiliation":[{"name":"School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ting-Zhu","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liang-Jian","family":"Deng","sequence":"additional","affiliation":[{"name":"School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xi-Le","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,2,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2119","DOI":"10.1109\/TGRS.2003.817206","article-title":"Destriping CMODIS data by power filtering","volume":"41","author":"Chen","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"8567","DOI":"10.1364\/OE.17.008567","article-title":"Stripe and ring artifact removal with combined wavelet Fourier filtering","volume":"17","author":"Trtik","year":"2009","journal-title":"Opt. Express"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"620","DOI":"10.1016\/j.isprsjprs.2011.04.003","article-title":"De-striping hyperspectral imagery using wavelet transform and adaptive frequency domain filtering","volume":"66","year":"2011","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_4","first-page":"620","article-title":"Destriping of Hyperion images using low-pass-filter and local-brightness-normalization","volume":"66","author":"Pal","year":"2011","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2505","DOI":"10.1080\/01431160050030592","article-title":"Destriping multisensor imagery with moment matching","volume":"21","author":"Gadallah","year":"2000","journal-title":"Int. J. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/0146-664X(79)90035-2","article-title":"Destriping Landsat MSS images by histogram modification","volume":"10","author":"Horn","year":"1979","journal-title":"Comput. Graph. Image Process."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/0034-4257(89)90026-6","article-title":"Destriping GOES images by matching empirical distribution functions","volume":"29","author":"Weinreb","year":"1989","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"859","DOI":"10.1080\/01431169008955060","article-title":"Destriping multiple sensor imagery by improved histogram matching","volume":"11","author":"Wegener","year":"1990","journal-title":"Int. J. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"613","DOI":"10.1109\/TGRS.2008.2003436","article-title":"Restoration of Aqua MODIS band 6 using histogram matching and local least squares fitting","volume":"47","author":"Rakwatin","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"S68","DOI":"10.5589\/m07-067","article-title":"Automatic destriping of Hyperion imagery based on spectral moment matching","volume":"34","author":"Sun","year":"2008","journal-title":"Can. J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1080\/2150704X.2013.860564","article-title":"A piece-wise approach to removing the nonlinear and irregular stripes in MODIS data","volume":"35","author":"Shen","year":"2014","journal-title":"Int. J. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"4420","DOI":"10.1109\/TIP.2012.2206037","article-title":"Variational algorithms to remove stationary noise: applications to microscopy imaging","volume":"21","author":"Fehrenbach","year":"2012","journal-title":"IEEE Trans. Image Process."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"613","DOI":"10.1137\/130929424","article-title":"Processing stationary noise: model and parameter selection in variational methods","volume":"7","author":"Fehrenbach","year":"2014","journal-title":"SIAM J. Imaging Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1007\/s10851-016-0667-3","article-title":"A variational model for multiplicative structured noise removal","volume":"57","author":"Escande","year":"2017","journal-title":"J. Math. Imaging Vis."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1492","DOI":"10.1109\/TGRS.2008.2005780","article-title":"A MAP-based algorithm for destriping and inpainting of remotely sensed images","volume":"47","author":"Shen","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Chen, Y., Huang, T.Z., Zhao, X.L., Deng, L.J., and Huang, J. (2017). Stripe noise removal of remote sensing images by total variation regularization and group sparsity constraint. Remote Sens., 9.","DOI":"10.3390\/rs9060559"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2924","DOI":"10.1109\/TGRS.2011.2119399","article-title":"Toward optimal destriping of MODIS data using a unidirectional variational model","volume":"49","author":"Bouali","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"4729","DOI":"10.1109\/TGRS.2013.2284280","article-title":"Hyperspectral image restoration using low-rank matrix recovery","volume":"52","author":"Zhang","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2756","DOI":"10.1016\/j.ijleo.2013.11.031","article-title":"Removal of stripe noise with spatially adaptive unidirectional total variation","volume":"125","author":"Zhou","year":"2014","journal-title":"Opt. Int. J. Light Electron Opt."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Liu, H., Zhang, Z.L., Liu, S.Y., Liu, T.T., and Chang, Y. (2015, January 27\u201330). Destriping algorithm with L0 sparsity prior for remote sensing images. Proceedings of the IEEE International Conference on Image Processing (ICIP), Quebec City, QC, Canada.","DOI":"10.1109\/ICIP.2015.7351211"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1051","DOI":"10.1109\/LGRS.2013.2285124","article-title":"Simultaneous destriping and denoising for remote sensing images with unidirectional total variation and sparse representation","volume":"11","author":"Chang","year":"2014","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1852","DOI":"10.1109\/TIP.2015.2404782","article-title":"Anisotropic Spectral-Spatial Total Variation Model for Multispectral Remote Sensing Image Destriping","volume":"24","author":"Chang","year":"2015","journal-title":"IEEE Trans. Image Process."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1109\/TGRS.2015.2452812","article-title":"Total-variation-regularized low-rank matrix factorization for hyperspectral image restoration","volume":"54","author":"He","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1016\/j.automatica.2016.08.014","article-title":"Sparse plus low rank network identification: A nonparametric approach","volume":"76","author":"Zorzi","year":"2017","journal-title":"Automatica"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2327","DOI":"10.1109\/TAC.2015.2491678","article-title":"AR identification of latent-variable graphical models","volume":"61","author":"Zorzi","year":"2016","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3049","DOI":"10.1109\/TGRS.2015.2510418","article-title":"Stripe Noise Separation and Removal in Remote Sensing Images by Consideration of the Global Sparsity and Local Variational Properties","volume":"54","author":"Liu","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"7018","DOI":"10.1109\/TGRS.2016.2594080","article-title":"Remote Sensing Image Stripe Noise Removal: From Image Decomposition Perspective","volume":"54","author":"Chang","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"232","DOI":"10.1016\/j.ins.2014.10.041","article-title":"Image restoration using total variation with overlapping group sparsity, Information Sciences","volume":"295","author":"Liu","year":"2015","journal-title":"Inf. Sci."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"743","DOI":"10.1007\/s10915-017-0460-5","article-title":"Cauchy noise removal by nonconvex ADMM with convergence guarantees","volume":"74","author":"Mei","year":"2018","journal-title":"J. Sci. Comput."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"410","DOI":"10.1016\/j.apm.2017.04.002","article-title":"A non-convex tensor rank approximation for tensor completion","volume":"48","author":"Ji","year":"2017","journal-title":"Appl. Math. Model."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1860","DOI":"10.1109\/TGRS.2009.2033587","article-title":"Statistical linear destriping of satellite-based pushbroom-type images","volume":"48","author":"Carfantan","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1016\/0167-2789(92)90242-F","article-title":"Nonlinear total variation based noise removal algorithms","volume":"60","author":"Rudin","year":"1992","journal-title":"Phys. D Nonlinear Phenom."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"4045","DOI":"10.1109\/TGRS.2012.2227764","article-title":"Deblurring and sparse unmixing for hyperspectral images","volume":"51","author":"Zhao","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1016\/j.ins.2017.04.049","article-title":"Image Deblurring With an Inaccurate Blur Kernel Using a Group-Based Low-Rank Image Prior","volume":"408","author":"Ma","year":"2017","journal-title":"Inf. Sci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"147","DOI":"10.5201\/ipol.2012.g-tvi","article-title":"Total variation inpainting using split Bregman","volume":"2","author":"Getreuer","year":"2012","journal-title":"Image Process. Line"},{"key":"ref_36","unstructured":"Yuan, G.Z., and Ghanem, B. (2015, January 7\u201312). l0TV: A new method for image restoration in the presence of impulse noise. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Boston, MA, USA."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1109\/MGRS.2015.2441912","article-title":"Missing information reconstruction of remote sensing data: A technical review","volume":"3","author":"Shen","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"350","DOI":"10.1007\/s10915-012-9597-4","article-title":"An efficient algorithm for \u21130 minimization in wavelet frame based image restoration","volume":"54","author":"Dong","year":"2013","journal-title":"J. Sci. Comput."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"3170","DOI":"10.1016\/j.jfranklin.2017.01.037","article-title":"Cartoon-texture image decomposition via non-convex low-rank texture regularization","volume":"354","author":"Fan","year":"2017","journal-title":"J. Frankl. Inst."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2448","DOI":"10.1137\/100808071","article-title":"Sparse approximation via penalty decomposition methods","volume":"23","author":"Lu","year":"2013","journal-title":"SIAM J. Optim."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"613","DOI":"10.1109\/18.382009","article-title":"De-noising by soft-thresholding","volume":"41","author":"Donoho","year":"1995","journal-title":"IEEE Trans. Inf. Theory"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIP.2003.819861","article-title":"Image Quality Assesment: From Error Visibility to Structural Similarity","volume":"13","author":"Wang","year":"2004","journal-title":"IEEE Trans. Image Process."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"700","DOI":"10.1137\/110836936","article-title":"On the O(1\/n) Convergence Rate of the Douglas Rachford Alternating Direction Method","volume":"50","author":"He","year":"2012","journal-title":"SIAM J. Numer. Anal."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"889","DOI":"10.1007\/s10915-015-0048-x","article-title":"On the global and linear convergence of the generalized alternating direction method of multipliers","volume":"663","author":"Deng","year":"2016","journal-title":"J. Sci. Comput."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"115010","DOI":"10.1088\/0266-5611\/28\/11\/115010","article-title":"Alternating direction methods for classical and ptychographic phase retrieval","volume":"28","author":"Wen","year":"2012","journal-title":"Inverse Probl."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"946","DOI":"10.1137\/110853996","article-title":"Hankel matrix rank minimization with applications to system identification and realization","volume":"34","author":"Fazel","year":"2013","journal-title":"SIAM J. Matrix Anal. 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