{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T00:37:57Z","timestamp":1774053477412,"version":"3.50.1"},"reference-count":41,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2020,12,30]],"date-time":"2020-12-30T00:00:00Z","timestamp":1609286400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the State Key Program of National Natural Science of China","award":["61836009"],"award-info":[{"award-number":["61836009"]}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1701267"],"award-info":[{"award-number":["U1701267"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61671350"],"award-info":[{"award-number":["61671350"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62006179"],"award-info":[{"award-number":["62006179"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the China Postdoctoral Science Special funded project","award":["2020T130492"],"award-info":[{"award-number":["2020T130492"]}]},{"name":"the China Postdoctoral Science Foundation funded project","award":["2019M663634"],"award-info":[{"award-number":["2019M663634"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Recently, with the popularity of space-borne earth satellites, the resolution of high-resolution panchromatic (PAN) and multispectral (MS) remote sensing images is also increasing year by year, multiresolution remote sensing classification has become a research hotspot. In this paper, from the perspective of deep learning, we design a dual-branch interactive spatial-channel collaborative attention enhancement network (SCCA-net) for multiresolution classification. It aims to combine sample enhancement and feature enhancement to improve classification accuracy. In the part of sample enhancement, we propose an adaptive neighbourhood transfer sampling strategy (ANTSS). Different from the traditional pixel-centric sampling strategy with orthogonal sampling angle, our algorithm allows each patch to adaptively transfer the neighbourhood range by finding the homogeneous region of the pixel to be classified. And it also adaptively adjust the sampling angle according to the texture distribution of the homogeneous region to capture neighbourhood information that is more conducive for classification. Moreover, in the part of feature enhancement part, we design a local spatial attention module (LSA-module) for PAN data to highlight the spatial resolution advantages and a global channel attention module (GCA-module) for MS data to improve the multi-channel representation. It not only highlights the spatial resolution advantage of PAN data and the multi-channel advantage of MS data, but also improves the difference between features through the interaction between the two modules. Quantitative and qualitative experimental results verify the robustness and effectiveness of the method.<\/jats:p>","DOI":"10.3390\/rs13010106","type":"journal-article","created":{"date-parts":[[2020,12,30]],"date-time":"2020-12-30T20:13:41Z","timestamp":1609359221000},"page":"106","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["A Spatial-Channel Collaborative Attention Network for Enhancement of Multiresolution Classification"],"prefix":"10.3390","volume":"13","author":[{"given":"Wenping","family":"Ma","sequence":"first","affiliation":[{"name":"The Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi\u2019an 710071, China"}]},{"given":"Jiliang","family":"Zhao","sequence":"additional","affiliation":[{"name":"The Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi\u2019an 710071, China"}]},{"given":"Hao","family":"Zhu","sequence":"additional","affiliation":[{"name":"The Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi\u2019an 710071, China"}]},{"given":"Jianchao","family":"Shen","sequence":"additional","affiliation":[{"name":"The Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi\u2019an 710071, China"}]},{"given":"Licheng","family":"Jiao","sequence":"additional","affiliation":[{"name":"The Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi\u2019an 710071, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3459-5079","authenticated-orcid":false,"given":"Yue","family":"Wu","sequence":"additional","affiliation":[{"name":"The Xi\u2019an Key Laboratory of Big Data and Intelligent Vision, Xidian University, School of Computer Science and Technology, Xi\u2019an 710071, China"}]},{"given":"Biao","family":"Hou","sequence":"additional","affiliation":[{"name":"The Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi\u2019an 710071, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,12,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1204","DOI":"10.1109\/36.763274","article-title":"Multiresolution-based image fusion with additive wavelet decomposition","volume":"37","author":"Nunez","year":"1999","journal-title":"IEEE Trans. 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