{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T13:48:26Z","timestamp":1767707306619,"version":"build-2065373602"},"reference-count":45,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2021,7,3]],"date-time":"2021-07-03T00:00:00Z","timestamp":1625270400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000271","name":"Science and Technology Facilities Council","doi-asserted-by":"publisher","award":["ST\/K000977\/1","KEI2019-03-01"],"award-info":[{"award-number":["ST\/K000977\/1","KEI2019-03-01"]}],"id":[{"id":"10.13039\/501100000271","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100011690","name":"UK Space Agency","doi-asserted-by":"publisher","award":["ST\/S001891\/1","RP10G0435A05","RP10G0435C206"],"award-info":[{"award-number":["ST\/S001891\/1","RP10G0435A05","RP10G0435C206"]}],"id":[{"id":"10.13039\/100011690","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Higher spatial resolution imaging data are considered desirable in many Earth observation applications. In this work, we propose and demonstrate the TARSGAN (learning Terrestrial image deblurring using Adaptive weighted dense Residual Super-resolution Generative Adversarial Network) system for Super-resolution Restoration (SRR) of 10 m\/pixel Sentinel-2 \u201ctrue\u201d colour images as well as all the other multispectral bands. In parallel, the ELF (automated image Edge detection and measurements of edge spread function, Line spread function, and Full width at half maximum) system is proposed to achieve automated and precise assessments of the effective resolutions of the input and SRR images. Subsequent ELF measurements of the TARSGAN SRR results suggest an averaged effective resolution enhancement factor of about 2.91 times (equivalent to ~3.44 m\/pixel for the 10 m\/pixel bands) given a nominal SRR upscaling factor of 4 times. Several examples are provided for different types of scenes from urban landscapes to agricultural scenes and sea-ice floes.<\/jats:p>","DOI":"10.3390\/rs13132614","type":"journal-article","created":{"date-parts":[[2021,7,4]],"date-time":"2021-07-04T22:35:22Z","timestamp":1625438122000},"page":"2614","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Towards Streamlined Single-Image Super-Resolution: Demonstration with 10 m Sentinel-2 Colour and 10\u201360 m Multi-Spectral VNIR and SWIR Bands"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9170-6655","authenticated-orcid":false,"given":"Yu","family":"Tao","sequence":"first","affiliation":[{"name":"Imaging Group, Mullard Space Science Laboratory, Department of Space and Climate Physics, University College London, Holmbury St Mary, Surrey RH5 6NT, UK"}]},{"given":"Siting","family":"Xiong","sequence":"additional","affiliation":[{"name":"College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3744-695X","authenticated-orcid":false,"given":"Rui","family":"Song","sequence":"additional","affiliation":[{"name":"Imaging Group, Mullard Space Science Laboratory, Department of Space and Climate Physics, University College London, Holmbury St Mary, Surrey RH5 6NT, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5077-3736","authenticated-orcid":false,"given":"Jan-Peter","family":"Muller","sequence":"additional","affiliation":[{"name":"Imaging Group, Mullard Space Science Laboratory, Department of Space and Climate Physics, University College London, Holmbury St Mary, Surrey RH5 6NT, UK"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1039","DOI":"10.1016\/j.imavis.2006.02.026","article-title":"Image super-resolution survey","volume":"24","year":"2006","journal-title":"Image Vis. 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