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HSI super-resolution (SR) aims to enhance the spatial resolution of the HSIs without modifying the equipment and has become a hot issue for HSI processing. In this paper, inspired by two important observations, a gated content-oriented residual dense network (GCoRDN) is designed for the HSI SR. To be specific, based on the observation that the structure and texture exhibit different sensitivities to the spatial degradation, a content-oriented network with two branches is designed. Meanwhile, a weight-sharing strategy is merged in the network to preserve the consistency in the structure and the texture. In addition, based on the observation of the super-resolved results, a gating mechanism is applied as a form of post-processing to further enhance the SR performance. Experimental results and data analysis on both ground-based HSIs and airborne HSIs have demonstrated the effectiveness of the proposed method.<\/jats:p>","DOI":"10.3390\/rs15133378","type":"journal-article","created":{"date-parts":[[2023,7,3]],"date-time":"2023-07-03T00:49:27Z","timestamp":1688345367000},"page":"3378","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Gated Content-Oriented Residual Dense Network for Hyperspectral Image Super-Resolution"],"prefix":"10.3390","volume":"15","author":[{"given":"Jing","family":"Hu","sequence":"first","affiliation":[{"name":"The Shaanxi Key Laboratory for Network Computing and Security Technology, School of Computer Science and Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}]},{"given":"Tingting","family":"Li","sequence":"additional","affiliation":[{"name":"The Shaanxi Key Laboratory for Network Computing and Security Technology, School of Computer Science and Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}]},{"given":"Minghua","family":"Zhao","sequence":"additional","affiliation":[{"name":"The Shaanxi Key Laboratory for Network Computing and Security Technology, School of Computer Science and Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}]},{"given":"Fei","family":"Wang","sequence":"additional","affiliation":[{"name":"The Shaanxi Key Laboratory for Network Computing and Security Technology, School of Computer Science and Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}]},{"given":"Jiawei","family":"Ning","sequence":"additional","affiliation":[{"name":"The Shaanxi Key Laboratory for Network Computing and Security Technology, School of Computer Science and Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,2]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"A Stepwise Domain Adaptive Segmentation Network With Covariate Shift Alleviation for Remote Sensing Imagery","volume":"60","author":"Li","year":"2022","journal-title":"IEEE Trans. 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