{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T20:22:38Z","timestamp":1773001358410,"version":"3.50.1"},"reference-count":37,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T00:00:00Z","timestamp":1763510400000},"content-version":"vor","delay-in-days":322,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100011789","name":"Department of Science and Technology of Jilin Province","doi-asserted-by":"publisher","award":["20250102243JC"],"award-info":[{"award-number":["20250102243JC"]}],"id":[{"id":"10.13039\/501100011789","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62062064"],"award-info":[{"award-number":["62062064"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010211","name":"Education Department of Jilin Province","doi-asserted-by":"publisher","award":["JJKH20250414KJ"],"award-info":[{"award-number":["JJKH20250414KJ"]}],"id":[{"id":"10.13039\/501100010211","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Intelligent Systems"],"published-print":{"date-parts":[[2025,1]]},"abstract":"<jats:p>Because of the copyright issues of hyperspectral images continue to rise, in this paper, we propose to use a neural network\u2013based watermarking model to protect the copyright. By applying normalization\u2010based attention module (NAM) to deep dispersed watermarking with synchronization and fusion (DWSF), a NDWSF model is proposed for robust hyperspectral image watermarking. It consists of encoding, decoding, discrimination, and attack modules. The encoding and decoding modules are used for embedding and extracting watermarks. Discrimination module is proposed for improving the quality of watermarked image. The discrimination module and the encoding module are in an adversarial relationship to motivate the encoder to generate watermarks with stronger invisibility. Attack module is employed between embedding and extraction to improve robustness against compression and noise and geometric attacks. In order to more effectively utilize image features for watermarking, a kind of hybrid attention mechanism is employed in embedding and extraction by adding NAM. Experimental results show that the loss convergence and stability in training is improved. The peak signal\u2010to\u2010noise ratio of the proposed method is 48.08\u2009dB, higher than other methods about 2.5\u2009dB. The bit error rate of the proposed method is less than 2.5% for various hybrid attacks, showing good robustness.<\/jats:p>","DOI":"10.1155\/int\/8844705","type":"journal-article","created":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T06:21:26Z","timestamp":1763619686000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Robust Watermarking Method for Hyperspectral Images Based on Hybrid Attention Mechanism"],"prefix":"10.1155","volume":"2025","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4360-4010","authenticated-orcid":false,"given":"De","family":"Li","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0000-4757-7534","authenticated-orcid":false,"given":"Zhewei","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0008-1573-3625","authenticated-orcid":false,"given":"Xuanyou","family":"Li","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5908-8321","authenticated-orcid":false,"given":"Xun","family":"Jin","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0005-4261-1285","authenticated-orcid":false,"given":"Yanwei","family":"Wang","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2025,11,19]]},"reference":[{"key":"e_1_2_11_1_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12145-024-01684-x"},{"key":"e_1_2_11_2_2","doi-asserted-by":"crossref","unstructured":"PanthakkanA. AnzarS. M. Al MansooriS. andAl AhmadH. Preserving the Integrity of Hyperspectral Satellite Imagery Using a Secure and Efficient Reversible Watermarking Technique for Ownership Protection IEEE International Conference Expo Real-Time Communication 2023 IIT (RTC) 1\u20135.","DOI":"10.1109\/RTC58825.2023.10304241"},{"key":"e_1_2_11_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.heliyon.2024.e33208"},{"key":"e_1_2_11_4_2","doi-asserted-by":"publisher","DOI":"10.3390\/technologies13050170"},{"key":"e_1_2_11_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/jstars.2020.2999057"},{"key":"e_1_2_11_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.image.2021.116523"},{"key":"e_1_2_11_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/mgrs.2021.3105440"},{"key":"e_1_2_11_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.aeue.2004.11.040"},{"key":"e_1_2_11_9_2","doi-asserted-by":"crossref","unstructured":"FangH.andZhouQ. 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