{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:14:22Z","timestamp":1760148862012,"version":"build-2065373602"},"reference-count":64,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2023,6,12]],"date-time":"2023-06-12T00:00:00Z","timestamp":1686528000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2021YFA0715203","62271087","2021JJ40609","kq2208403","21B0330"],"award-info":[{"award-number":["2021YFA0715203","62271087","2021JJ40609","kq2208403","21B0330"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2021YFA0715203","62271087","2021JJ40609","kq2208403","21B0330"],"award-info":[{"award-number":["2021YFA0715203","62271087","2021JJ40609","kq2208403","21B0330"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Hunan Provincial Natural Science Foundation Project","award":["2021YFA0715203","62271087","2021JJ40609","kq2208403","21B0330"],"award-info":[{"award-number":["2021YFA0715203","62271087","2021JJ40609","kq2208403","21B0330"]}]},{"name":"Changsha Municipal Natural Science Foundation","award":["2021YFA0715203","62271087","2021JJ40609","kq2208403","21B0330"],"award-info":[{"award-number":["2021YFA0715203","62271087","2021JJ40609","kq2208403","21B0330"]}]},{"name":"Scientific Research Project of Hunan Education Department of China","award":["2021YFA0715203","62271087","2021JJ40609","kq2208403","21B0330"],"award-info":[{"award-number":["2021YFA0715203","62271087","2021JJ40609","kq2208403","21B0330"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Many hyperspectral image (HSI) super-resolution (SR) methods have been proposed and have achieved good results; however, they do not sufficiently preserve the spectral information. It is beneficial to sufficiently utilize the spectral correlation. In addition, most works super-resolve hyperspectral images using high computation complexity. To solve the above problems, a novel method based on a channel multilayer perceptron (CMLP) is presented in this article, which aims to obtain a better performance while reducing the computational cost. To sufficiently extract spectral features, a local-global spectral integration block is proposed, which consists of CMLP and some parameter-free operations. The block can extract local and global spectral features with low computational cost. In addition, a spatial feature group extraction block based on the CycleMLP framework is designed; it can extract local spatial features well and reduce the computation complexity and number of parameters. Extensive experiments demonstrate that our method achieves a good performance compared with other methods.<\/jats:p>","DOI":"10.3390\/rs15123066","type":"journal-article","created":{"date-parts":[[2023,6,13]],"date-time":"2023-06-13T02:00:45Z","timestamp":1686621645000},"page":"3066","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Spectral-Spatial MLP Network for Hyperspectral Image Super-Resolution"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-7780-430X","authenticated-orcid":false,"given":"Yunze","family":"Yao","sequence":"first","affiliation":[{"name":"College of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410114, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9849-1327","authenticated-orcid":false,"given":"Jianwen","family":"Hu","sequence":"additional","affiliation":[{"name":"College of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410114, China"}]},{"given":"Yaoting","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410114, China"}]},{"given":"Yushan","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410114, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1109\/LGRS.2013.2251316","article-title":"Classification Based on 3-D DWT and Decision Fusion for Hyperspectral Image Analysis","volume":"11","author":"Ye","year":"2014","journal-title":"IEEE Geosci. 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