{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T17:52:35Z","timestamp":1785952355756,"version":"3.56.0"},"reference-count":78,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100002920","name":"Hong Kong Research Grants Council","doi-asserted-by":"publisher","award":["9048123 (CityU 21211518)"],"award-info":[{"award-number":["9048123 (CityU 21211518)"]}],"id":[{"id":"10.13039\/501100002920","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002920","name":"Hong Kong Research Grants Council","doi-asserted-by":"publisher","award":["9042820 (CityU 11219019)"],"award-info":[{"award-number":["9042820 (CityU 11219019)"]}],"id":[{"id":"10.13039\/501100002920","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Macau Science and Technology Development Fund","award":["077\/2018\/A2"],"award-info":[{"award-number":["077\/2018\/A2"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Image Process."],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/tip.2020.3044214","type":"journal-article","created":{"date-parts":[[2020,12,17]],"date-time":"2020-12-17T20:54:07Z","timestamp":1608238447000},"page":"1423-1438","source":"Crossref","is-referenced-by-count":99,"title":["Hyperspectral Image Super-Resolution via Deep Progressive Zero-Centric Residual Learning"],"prefix":"10.1109","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0726-4522","authenticated-orcid":false,"given":"Zhiyu","family":"Zhu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3431-2021","authenticated-orcid":false,"given":"Junhui","family":"Hou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8419-4620","authenticated-orcid":false,"given":"Jie","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2802-7745","authenticated-orcid":false,"given":"Huanqiang","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6015-2618","authenticated-orcid":false,"given":"Jiantao","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2010.2046811"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2003.819861"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58526-6_13"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2862629"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2908968"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1016\/j.jag.2012.01.013"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.05.051"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995660"},{"key":"ref38","doi-asserted-by":"crossref","first-page":"1139","DOI":"10.3390\/rs9111139","article-title":"Hyperspectral image spatial super-resolution via 3D full convolutional neural network","volume":"9","author":"mei","year":"2017","journal-title":"Remote Sens"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.5721\/EuJRS20154809"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1109\/JSTARS.2019.2911113"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.08.019"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2014.2381272"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2885616"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1364\/JOSAA.16.000467"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2017.2668299"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2957527"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2018.2876362"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2855418"},{"key":"ref60","first-page":"137","article-title":"Fast light field reconstruction with deep coarse-to-fine modeling of spatial-angular clues","author":"yeung","year":"2018","journal-title":"Proc Eur Conf Comput Vis (ECCV)"},{"key":"ref62","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015","journal-title":"arXiv 1502 03167"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.37"},{"key":"ref63","first-page":"9","article-title":"Efficient backprop","author":"lecun","year":"2012","journal-title":"Neural Networks"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/S0083-6656(97)00038-X"},{"key":"ref64","article-title":"Layer normalization","author":"lei ba","year":"2016","journal-title":"arXiv 1607 06450"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2016.7532876"},{"key":"ref65","first-page":"3","article-title":"Group normalization","author":"wu","year":"2018","journal-title":"Proc Eur Conf Comput Vis (ECCV)"},{"key":"ref66","article-title":"Instance normalization: The missing ingredient for fast stylization","author":"ulyanov","year":"2016","journal-title":"arXiv 1607 08022"},{"key":"ref29","first-page":"1067","article-title":"Multiresolution wavelet decomposition i me merger of landsat thematic mapper and spot panchromatic data","volume":"62","author":"yocky","year":"1996","journal-title":"Photogramm Eng Remote Sens"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.151"},{"key":"ref68","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"arXiv 1412 6980"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2812999"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2014.2375320"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/MGRS.2013.2244672"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2855412"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1117\/12.565216"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.2986313"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/S1566-2535(01)00037-9"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2004.03.010"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2007.896687"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2010.09.003"},{"key":"ref50","first-page":"740","article-title":"Microsoft COCO: Common objects in context","author":"lin","year":"2014","journal-title":"In Proc European Conf Comp Vis"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2885236"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.3390\/rs9010067"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref56","first-page":"1","article-title":"Progressive growing of GANs for improved quality, stability, and variation","author":"karras","year":"2018","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.618"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00123"},{"key":"ref53","article-title":"Cascading and enhanced residual networks for accurate single-image super-resolution","author":"lan","year":"2020","journal-title":"IEEE Trans Cybern"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2968521"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2798162"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3015691"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00168"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00425"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2016.05.004"},{"key":"ref14","first-page":"382","article-title":"Exposure fusion","author":"kautz","year":"2007","journal-title":"Proc Pacific Conf Comput Graph Appl"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/36.763274"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/5.775414"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2016.2623626"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2016.2542360"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2013.6723732"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2014.2329767"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2019.2903448"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2878958"},{"key":"ref5","article-title":"Graph convolutional networks for hyperspectral image classification","author":"hong","year":"2020","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2010.2060550"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.150"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2017.2694159"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2011.2128330"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00266"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2017.68"},{"key":"ref48","first-page":"1060","article-title":"Multi-scale fusion algorithm comparisons: Pyramid, DWT and iterative DWT","author":"zheng","year":"2009","journal-title":"Proc IEEE Int Conf Inf Fusion"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2015.11.003"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.2973370"},{"key":"ref41","article-title":"Coupled convolutional neural network with adaptive response function learning for unsupervised hyperspectral super resolution","author":"zheng","year":"2020","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1364\/AO.54.000848"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2884076"}],"container-title":["IEEE Transactions on Image Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/83\/9263394\/09298460.pdf?arnumber=9298460","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:50:12Z","timestamp":1652194212000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9298460\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":78,"URL":"https:\/\/doi.org\/10.1109\/tip.2020.3044214","relation":{},"ISSN":["1057-7149","1941-0042"],"issn-type":[{"value":"1057-7149","type":"print"},{"value":"1941-0042","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}