Seite - 14 - in Document Image Processing

J. Imaging 2018,4, 68 15. Yi,H.;Brown,M.S.;Dong,X.User-assistedink-bleedreduction. IEEETrans. ImageProcess.2010,19,2646–2658. 16. Rowley-Brooke,R.;Pitié,F.;Kokaram,A.C. ANon-parametricFrameworkforDocumentBleed-through Removal. InProceedingsof the2013 IEEEConferenceonComputerVisionandPatternRecognition(CVPR), Portland,OR,USA,23–28 June2013;pp. 2954–2960. 17. Merrikh-Bayat, F.; Babaie-Zadeh,M.; Jutten, C. Linear-quadratic blind source separating structure for removingshow-throughinscanneddocuments. Int. J.Doc.Anal. Recognit. 2011,14, 319–333. [CrossRef] 18. Dubois,E.;Dano,P. Joint compressionandrestorationofdocumentswithbleed-through. InProceedingsof the2ndIS&TArchivingConference,Washington,DC,USA,26–29April2005;pp. 170–174. 19. Bertalmio,M.;Sapiro,G.;Caselles,V.;Ballester,C. ImageInpainting. InProceedingsof the2000SIGRAPH Conference,NewOrleans,LA,USA,23–28 July2000;pp. 417–424. 20. Criminisi,A.;Perez,P.;Toyama,K. Regionfillingandobject removalbyexemplar-based image inpainting. IEEETrans. ImageProcess. 2004,13, 1200–1212. [CrossRef] [PubMed] 21. Guillemot,C.;Meur,O.L. Image inpainting: Overviewand recent advances. IEEESignal Process. Mag. 2014,31, 127–144. [CrossRef] 22. Xu, Z.; Sun, J. Image inpaintingbypatchpropagationusingpatch sparsity. IEEETrans. ImageProcess. 2010,19, 1153–1165. [PubMed] 23. Shen,B.;Hu,W.;Zhang,Y.;Zhang,Y. Imageinpaintingviasparserepresentation. InProceedingsof the2009 IEEEInternationalConferenceonAcoustics,Speech,andSignalProcessing,Taipei,Taiwan,19–24April2009; pp. 697–700. 24. Walha,R.;Drira, F.; Lebourgeois, F.;Garcia,C.;Alimi,A.M. Jointdenoisingandmagnificationofnoisy Low-Resolution textual images. InProceedingsof the InternationalConferenceonDocumentAnalysisand Recognition,Tunis,Tunisia,23–26August2015. 25. Hoang,T.;BarneySmith,E.;Tabbone,S. Sparsity-basededgenoiseremoval frombilevelgraphicaldocument images. Int. J.Doc.Anal. Recognit. 2014,17, 161–179. [CrossRef] 26. Kumar,V.;Bansal,A.;Tulsiyan,G.H.;Mishra,A.;Namboodiri,A.; Jawahar,C.V.SparseDocument Image Coding for Restoration. In Proceedings of the International Conference onDocument Analysis and Recognition,Washington,DC,USA,28August2013. 27. Buades,A.;Coll,B.;Morel, J. Anon-localalgorithmfor imagedenoising. InProceedingsof the2005IEEE ComputerSocietyConferenceonComputerVisionandPatternRecognition(CVPR’05) ,SanDiego,CA,USA, 20–25 June2005;pp. 60–65. 28. Smith,S.;Brady, J. Susan—Anewapproachto lowlevel imageprocessing. Int. J.Comput.Vis.1997,23, 45–78. [CrossRef] 29. Jung,M.;Bresson,X.;Chan,T.F.;Vese,L.A.NonlocalMumford–Shahregularizers forcolor imagerestoration. IEEETrans. ImageProcess. 2011,20, 1583–1598. [CrossRef] [PubMed] 30. Zhang,X.;Burger,M.;Bresson,X.;Osher,S. Bregmanizednonlocal regularizationfordeconvolutionand sparsereconstruction. SIAMJ. ImageSci. 2010,3, 253–276. [CrossRef] 31. Zhang, J.; Zhao, D.; Gao, W. Group-based sparse representation for image restoration. IEEE Trans. ImageProcess.2014,8, 3336–3351. [CrossRef] [PubMed] 32. Dong,W.; Zhang, L.; Shi, G.; Li, X. Nonlocally centralized sparse representation for image restoration. IEEETrans. ImageProcess. 2013,22, 1620–1630. [CrossRef] [PubMed] 33. Tonazzini, A.; Savino, P.; Salerno, E. A non-stationary densitymodel to separate overlapped texts in degradeddocuments. Signal ImageVideoProcess. 2015,9, 155–164. [CrossRef] 34. Gerace, I.; Palomba, C.; Tonazzini, A. An inpainting technique based on regularization to remove bleed-throughfromancientdocuments.InProceedingsofthe2016InternationalWorkshoponComputational Intelligence forMultimediaUnderstanding(IWCIM),ReggioCalabria, Italy,27–28October2016;pp. 1–5. 35. Elad,M.;Aharon,M. Imagedenoisingviasparseandredundantrepresentationsover leanreddictionaries. IEEETrans. ImageProcess. 2006,15, 3736–3745. [CrossRef] [PubMed] 36. Mairal, J.;Elad,M.;Sapiro,G. Sparserepresentationforcolor imagerestoration. IEEETrans. ImageProcess. 2008,17, 53–69. [CrossRef] [PubMed] 37. Ravishankar,S.;Bresler,Y.MRimagereconstructionfromhighlyundersampledk-spacedatabydictionary learning. IEEETrans.Med. Imag. 2011,30, 1028–1041. [CrossRef] [PubMed] 14