{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T12:17:11Z","timestamp":1771330631769,"version":"3.50.1"},"reference-count":46,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2021,7,8]],"date-time":"2021-07-08T00:00:00Z","timestamp":1625702400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,7,8]],"date-time":"2021-07-08T00:00:00Z","timestamp":1625702400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"name":"Xerox Chair in Imaging Science"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["IJDAR"],"published-print":{"date-parts":[[2021,9]]},"DOI":"10.1007\/s10032-021-00379-z","type":"journal-article","created":{"date-parts":[[2021,7,8]],"date-time":"2021-07-08T20:02:20Z","timestamp":1625774540000},"page":"181-195","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Revealing a history: palimpsest text separation with generative networks"],"prefix":"10.1007","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7860-0183","authenticated-orcid":false,"given":"Anna","family":"Starynska","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Messinger","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu","family":"Kong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,7,8]]},"reference":[{"key":"379_CR1","unstructured":"Akbarinia, A., Gegenfurtner, K.R.: How is contrast encoded in deep neural networks? arXiv preprint arXiv:1809.01438 (2018)"},{"key":"379_CR2","unstructured":"Anirudh, R., Thiagarajan, J.J., Kailkhura, B., Bremer, T.: An unsupervised approach to solving inverse problems using generative adversarial networks. arXiv preprint arXiv:1805.07281 (2018)"},{"key":"379_CR3","unstructured":"Arandjelovi\u0107, R., Zisserman, A.: Object discovery with a copy-pasting gan. arXiv preprint arXiv:1905.11369 (2019)"},{"key":"379_CR4","doi-asserted-by":"crossref","unstructured":"Asim, M., Shamshad, F., Ahmed, A.: Blind image deconvolution using deep generative priors. In: 30th British Machine Vision Conference (2019)","DOI":"10.1109\/TCI.2020.3032671"},{"key":"379_CR5","unstructured":"Bora, A., Jalal, A., Price, E., Dimakis, A.G.: Compressed sensing using generative models. In: Proceedings of the 34th International Conference on Machine Learning-Volume 70, pp. 537\u2013546. JMLR. org (2017)"},{"key":"379_CR6","first-page":"5","volume":"2","author":"A Bora","year":"2018","unstructured":"Bora, A., Price, E., Dimakis, A.G.: Ambientgan: generative models from lossy measurements. ICLR 2, 5 (2018)","journal-title":"ICLR"},{"key":"379_CR7","unstructured":"Chollet, F., et\u00a0al.: Keras. https:\/\/keras.io (2015)"},{"key":"379_CR8","unstructured":"Easton, R.L., Christens-Barry, W.A., Knox, K.T.: Spectral image processing and analysis of the archimedes palimpsest. In: 2011 19th European Signal Processing Conference, pp. 1440\u20131444. IEEE (2011)"},{"key":"379_CR9","doi-asserted-by":"crossref","unstructured":"Easton, R.L., Knox, K.T., Christens-Barry, W.A., Boydston, K., Toth, M.B., Emery, D., Noel, W.: Standardized system for multispectral imaging of palimpsests. In: Computer Vision and Image Analysis of Art, vol. 7531, p. 75310D. International Society for Optics and Photonics (2010)","DOI":"10.1117\/12.839116"},{"key":"379_CR10","doi-asserted-by":"crossref","unstructured":"Fogel, S., Averbuch-Elor, H., Cohen, S., Mazor, S., Litman, R.: Scrabblegan: semi-supervised varying length handwritten text generation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4324\u20134333 (2020)","DOI":"10.1109\/CVPR42600.2020.00438"},{"key":"379_CR11","doi-asserted-by":"crossref","unstructured":"Gandelsman, Y., Shocher, A., Irani, M.: Double-dip: unsupervised image decomposition via coupled deep-image-priors. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol.\u00a06, p.\u00a02 (2019)","DOI":"10.1109\/CVPR.2019.01128"},{"issue":"PUBDB\u20132015\u20130632","key":"379_CR12","first-page":"104","volume":"7","author":"L Glaser","year":"2014","unstructured":"Glaser, L., Deckers, D.: The basics of fast-scanning XRF element mapping for iron-gall ink palimpsests. Manuscr. Cult. 7(PUBDB\u20132015\u201306320), 104\u2013112 (2014)","journal-title":"Manuscr. Cult."},{"key":"379_CR13","unstructured":"Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: Generative adversarial nets. In: Advances in Neural Information Processing Systems, pp. 2672\u20132680 (2014)"},{"key":"379_CR14","unstructured":"Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., Bengio, Y.: Generative adversarial nets. In: NIPS, pp. 2672\u20132680 (2014)"},{"key":"379_CR15","doi-asserted-by":"crossref","unstructured":"Hanif, M., Tonazzini, A., Savino, P., Salerno, E.: Sparse representation based inpainting for the restoration of document images affected by bleed-through. In: Multidisciplinary Digital Publishing Institute Proceedings, vol.\u00a02, p.\u00a093 (2018)","DOI":"10.3390\/proceedings2020093"},{"key":"379_CR16","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1016\/j.patcog.2019.01.025","volume":"91","author":"S He","year":"2019","unstructured":"He, S., Schomaker, L.: Deepotsu: document enhancement and binarization using iterative deep learning. Pattern Recognit. 91, 379\u2013390 (2019)","journal-title":"Pattern Recognit."},{"key":"379_CR17","unstructured":"Hollaus, F., Gau, M., Sablatnig, R., Christens-Barry, W.A., Miklas, H.: Readability enhancement and palimpsest decipherment of historical manuscripts. Kodikologie und Pal\u00e4ographie im Digitalen Zeitalter 3: Codicology and Palaeography in the Digital Age, vol. 3, p.\u00a031 (2015)"},{"key":"379_CR18","doi-asserted-by":"crossref","first-page":"446","DOI":"10.1016\/j.amc.2013.09.048","volume":"225","author":"B Jacobs","year":"2013","unstructured":"Jacobs, B., Momoniat, E.: A novel approach to text binarization via a diffusion-based model. Appl. Math. Comput. 225, 446\u2013460 (2013)","journal-title":"Appl. Math. Comput."},{"key":"379_CR19","unstructured":"Kingma, D.P., Welling, M.: Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114 (2013)"},{"key":"379_CR20","doi-asserted-by":"crossref","unstructured":"Kong, Q., Xu, Y., Wang, W., Jackson, P.J., Plumbley, M.D.: Single-channel signal separation and deconvolution with generative adversarial networks. In: Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19) (2019)","DOI":"10.24963\/ijcai.2019\/381"},{"issue":"11","key":"379_CR21","doi-asserted-by":"publisher","first-page":"2278","DOI":"10.1109\/5.726791","volume":"86","author":"Y LeCun","year":"1998","unstructured":"LeCun, Y., Bottou, L., Bengio, Y., Haffner, P.: Gradient-based learning applied to document recognition. Proc. IEEE 86(11), 2278\u20132324 (1998)","journal-title":"Proc. IEEE"},{"key":"379_CR22","unstructured":"Lettner, M., Sablatnig, R.: Multispectral imaging for analyzing ancient manuscripts. In: 2009 17th European Signal Processing Conference, pp. 1200\u20131204. IEEE (2009)"},{"key":"379_CR23","doi-asserted-by":"crossref","unstructured":"Li, J., Cui, R., Li, Y., Li, B., Du, Q., Ge, C.: Multitemporal hyperspectral image super-resolution through 3d generative adversarial network. In: 2019 10th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiTemp), pp. 1\u20134. IEEE (2019)","DOI":"10.1109\/Multi-Temp.2019.8866956"},{"key":"379_CR24","unstructured":"Li, S.C.X., Jiang, B., Marlin, B.: Misgan: learning from incomplete data with generative adversarial networks. In: ICLR (2019)"},{"key":"379_CR25","unstructured":"Lunz, S., \u00d6ktem, O., Sch\u00f6nlieb, C.B.: Adversarial regularizers in inverse problems. In: NIPS, pp. 8507\u20138516 (2018)"},{"key":"379_CR26","unstructured":"Mindermann, S.: Hyperspectral imaging for readability enhancement of historic manuscripts. Ph.D. thesis, Technical University of Munich (2018)"},{"issue":"4","key":"379_CR27","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1007\/s10032-008-0076-2","volume":"11","author":"RF Moghaddam","year":"2009","unstructured":"Moghaddam, R.F., Cheriet, M.: Low quality document image modeling and enhancement. Int. J. Doc. Anal. Recognit. (IJDAR) 11(4), 183\u2013201 (2009)","journal-title":"Int. J. Doc. Anal. Recognit. (IJDAR)"},{"key":"379_CR28","doi-asserted-by":"crossref","unstructured":"Pajot, A., de\u00a0Bezenac, E., Gallinari, P.: Unsupervised adversarial image reconstruction. In: ICLR (2019)","DOI":"10.1088\/1742-5468\/ab3195"},{"key":"379_CR29","doi-asserted-by":"crossref","unstructured":"Rapantzikos, K., Balas, C.: Hyperspectral imaging: potential in non-destructive analysis of palimpsests. In: IEEE International Conference on Image Processing 2005, vol.\u00a02, pp. II\u2013618. IEEE (2005)","DOI":"10.1109\/ICIP.2005.1530131"},{"key":"379_CR30","doi-asserted-by":"crossref","unstructured":"Rick\u00a0Chang, J., Li, C.L., Poczos, B., Vijaya\u00a0Kumar, B., Sankaranarayanan, A.C.: One network to solve them all\u2013solving linear inverse problems using deep projection models. In: CVPR, pp. 5888\u20135897 (2017)","DOI":"10.1109\/ICCV.2017.627"},{"key":"379_CR31","doi-asserted-by":"publisher","unstructured":"Rochester Institute of Technology: Research computing services (2019). https:\/\/doi.org\/10.34788\/0S3G-QD15. https:\/\/www.rit.edu\/researchcomputing\/","DOI":"10.34788\/0S3G-QD15"},{"key":"379_CR32","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-net: convolutional networks for biomedical image segmentation. In: International Conference on Medical image computing and computer-assisted intervention, pp. 234\u2013241. Springer (2015)","DOI":"10.1007\/978-3-319-24574-4_28"},{"issue":"2\u20134","key":"379_CR33","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1007\/s10032-006-0028-7","volume":"9","author":"E Salerno","year":"2007","unstructured":"Salerno, E., Tonazzini, A., Bedini, L.: Digital image analysis to enhance underwritten text in the Archimedes palimpsest. Int. J. Doc. Anal. Recognit. (IJDAR) 9(2\u20134), 79\u201387 (2007)","journal-title":"Int. J. Doc. Anal. Recognit. (IJDAR)"},{"key":"379_CR34","unstructured":"\u201cSinai Greek 960\u201d sinai.library.ucla.edu, a publication of St. Catherine\u2019s Monastery of the Sinai in collaboration with EMEL and UCLA (2019). https:\/\/sinai.library.ucla.edu\/. Accessed 5 June (2019)"},{"key":"379_CR35","doi-asserted-by":"crossref","unstructured":"Soltani, M., Jain, S., Sambasivan, A.: Learning generative models of structured signals from their superposition using gans with application to denoising and demixing. arXiv preprint arXiv:1902.04664 (2019)","DOI":"10.1109\/IEEECONF44664.2019.9048875"},{"key":"379_CR36","doi-asserted-by":"crossref","unstructured":"Starynska, A., Easton\u00a0Jr, R.L., Messinger, D.: Methods of data augmentation for palimpsest character recognition with deep neural network. In: Proceedings of the 4th International Workshop on Historical Document Imaging and Processing, pp. 54\u201358. ACM (2017)","DOI":"10.1145\/3151509.3151515"},{"issue":"2","key":"379_CR37","doi-asserted-by":"publisher","first-page":"473","DOI":"10.1109\/TIP.2005.860323","volume":"15","author":"A Tonazzini","year":"2006","unstructured":"Tonazzini, A., Bedini, L., Salerno, E.: A Markov model for blind image separation by a mean-field EM algorithm. IEEE Trans. Image Process. 15(2), 473\u2013482 (2006)","journal-title":"IEEE Trans. Image Process."},{"issue":"1","key":"379_CR38","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1007\/s11760-014-0735-3","volume":"9","author":"A Tonazzini","year":"2015","unstructured":"Tonazzini, A., Savino, P., Salerno, E.: A non-stationary density model to separate overlapped texts in degraded documents. Signal Image Video Process. 9(1), 155\u2013164 (2015)","journal-title":"Signal Image Video Process."},{"issue":"12","key":"379_CR39","doi-asserted-by":"publisher","first-page":"1191","DOI":"10.1109\/34.476511","volume":"17","author":"OD Trier","year":"1995","unstructured":"Trier, O.D., Jain, A.K.: Goal-directed evaluation of binarization methods. IEEE Trans. Pattern Anal. Mach. Intell. 17(12), 1191\u20131201 (1995)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"379_CR40","unstructured":"Ulyanov, D., Vedaldi, A., Lempitsky, V.: Deep image prior. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2018)"},{"key":"379_CR41","doi-asserted-by":"crossref","unstructured":"Valdiviezo-N, J.C., Urcid, G.: Multispectral images segmentation of ancient documents with lattice memories. In: Digital Image Processing and Analysis, p. DMD6. Optical Society of America (2010)","DOI":"10.1364\/DIPA.2010.DMD6"},{"key":"379_CR42","unstructured":"Vatican palimpsests. https:\/\/spotlight.vatlib.it\/palimpsests\/"},{"key":"379_CR43","doi-asserted-by":"publisher","first-page":"e453","DOI":"10.7717\/peerj.453","volume":"2","author":"S Van der Walt","year":"2014","unstructured":"Van der Walt, S., Sch\u00f6nberger, J.L., Nunez-Iglesias, J., Boulogne, F., Warner, J.D., Yager, N., Gouillart, E., Yu, T.: scikit-image: image processing in python. PeerJ 2, e453 (2014)","journal-title":"PeerJ"},{"issue":"4","key":"379_CR44","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1109\/MSP.2008.924960","volume":"25","author":"DJ Walvoord","year":"2008","unstructured":"Walvoord, D.J., Easton, R.L.: Digital transcription of the Archimedes palimpsest [applications corner]. IEEE Signal Process. Mag. 25(4), 100\u2013104 (2008). https:\/\/doi.org\/10.1109\/MSP.2008.924960","journal-title":"IEEE Signal Process. Mag."},{"key":"379_CR45","doi-asserted-by":"crossref","unstructured":"Wu, K., Otoo, E., Shoshani, A.: Optimizing connected component labeling algorithms. In: Medical Imaging 2005: Image Processing, vol. 5747, pp. 1965\u20131977. International Society for Optics and Photonics (2005)","DOI":"10.1117\/12.596105"},{"key":"379_CR46","doi-asserted-by":"crossref","unstructured":"Yeh, R.A., Chen, C., Yian\u00a0Lim, T., Schwing, A.G., Hasegawa-Johnson, M., Do, M.N.: Semantic image inpainting with deep generative models. In: CVPR, pp. 5485\u20135493 (2017)","DOI":"10.1109\/CVPR.2017.728"}],"container-title":["International Journal on Document Analysis and Recognition (IJDAR)"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10032-021-00379-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10032-021-00379-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10032-021-00379-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,5]],"date-time":"2023-11-05T20:48:59Z","timestamp":1699217339000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10032-021-00379-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,8]]},"references-count":46,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2021,9]]}},"alternative-id":["379"],"URL":"https:\/\/doi.org\/10.1007\/s10032-021-00379-z","relation":{},"ISSN":["1433-2833","1433-2825"],"issn-type":[{"value":"1433-2833","type":"print"},{"value":"1433-2825","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,8]]},"assertion":[{"value":"18 November 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 May 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 June 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 July 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}