{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T15:28:01Z","timestamp":1780500481181,"version":"3.54.1"},"reference-count":52,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072345"],"award-info":[{"award-number":["62072345"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41671382"],"award-info":[{"award-number":["41671382"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100011297","name":"State Key Laboratory for Information Engineering in Surveying, Mapping, and Remote Sensing Special Research Funding","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100011297","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Geosci. Remote Sensing"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/tgrs.2023.3282186","type":"journal-article","created":{"date-parts":[[2023,6,2]],"date-time":"2023-06-02T19:39:42Z","timestamp":1685734782000},"page":"1-18","source":"Crossref","is-referenced-by-count":26,"title":["Hyperspectral Image Compression via Cross-Channel Contrastive Learning"],"prefix":"10.1109","volume":"61","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0223-9037","authenticated-orcid":false,"given":"Yuanyuan","family":"Guo","sequence":"first","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7944-8515","authenticated-orcid":false,"given":"Yanwen","family":"Chong","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6789-3876","authenticated-orcid":false,"given":"Shaoming","family":"Pan","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2007.894565"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2006.888109"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.577"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995660"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2018.2870980"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2016.2608780"},{"key":"ref10","doi-asserted-by":"crossref","first-page":"3272","DOI":"10.1109\/JSTARS.2018.2851368","article-title":"Tridiagonal folmat enhanced multivariance products representation based hyperspectral data compression","volume":"11","author":"g\u00fcndo?ar","year":"2018","journal-title":"IEEE J Sel Topics Appl Earth Observ Remote Sens"},{"key":"ref17","article-title":"End-to-end optimized image compression","author":"ball\u00e9","year":"2016","journal-title":"arXiv 1611 01704"},{"key":"ref16","article-title":"Variable rate image compression with recurrent neural networks","author":"toderici","year":"2015","journal-title":"arXiv 1511 06085"},{"key":"ref19","first-page":"1","article-title":"Joint autoregressive and hierarchical priors for learned image compression","volume":"31","author":"minnen","year":"2018","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref18","article-title":"Variational image compression with a scale hyperprior","author":"ball\u00e9","year":"2018","journal-title":"arXiv 1802 01436"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3112268"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3066485"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ACSSC.2003.1292216"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01453"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TCI.2020.2996075"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1016\/0034-4257(93)90013-N"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/EORSA.2008.4620308"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2010.2046811"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2021.3075956"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3031016"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1016\/j.isprsjprs.2019.09.006"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2008.2005824"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2005.859942"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2016.2613848"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2018.8519455"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1002\/j.1538-7305.1948.tb01338.x"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1080\/01431161.2014.968682"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2005.1526121"},{"key":"ref40","article-title":"Airborne hyperspectral data over Chikusei","volume":"5","author":"yokoya","year":"2016"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2022.3190209"},{"key":"ref34","first-page":"1597","article-title":"A simple framework for contrastive learning of visual representations","author":"chen","year":"2020","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref37","article-title":"Blind image super-resolution via contrastive representation learning","author":"zhang","year":"2021","journal-title":"arXiv 2107 00708"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01041"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00393"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58621-8_45"},{"key":"ref32","article-title":"Representation learning with contrastive predictive coding","author":"van den oord","year":"2018","journal-title":"arXiv 1807 03748"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2019.2924292"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jspr.2015.01.006"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2009.5459271"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1981.1056282"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.image.2021.116255"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.3034414"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.3390\/rs13214390"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.3390\/rs14102472"},{"key":"ref20","first-page":"11913","article-title":"High-fidelity generative image compression","volume":"33","author":"mentzer","year":"2020","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref22","article-title":"Learned image compression with discretized Gaussian-Laplacian-logistic mixture model and concatenated residual modules","author":"fu","year":"2021","journal-title":"arXiv 2107 06463"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00796"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/s13042-019-00937-2"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.3390\/rs12213657"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.50"}],"container-title":["IEEE Transactions on Geoscience and Remote Sensing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/36\/10006360\/10143262.pdf?arnumber=10143262","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,3]],"date-time":"2023-07-03T18:10:52Z","timestamp":1688407852000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10143262\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":52,"URL":"https:\/\/doi.org\/10.1109\/tgrs.2023.3282186","relation":{},"ISSN":["0196-2892","1558-0644"],"issn-type":[{"value":"0196-2892","type":"print"},{"value":"1558-0644","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}