{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T23:36:17Z","timestamp":1761176177357,"version":"build-2065373602"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686318","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T00:00:00Z","timestamp":1761004800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,10,21]]},"abstract":"<jats:p>Recent advances in Vision Mamba architectures have shown great promise for remote sensing image super-resolution (RSISR), owing to their efficient state space modeling. However, existing Mamba-based methods face two critical challenges: inadequate cross-layer feature transmission and limited frequency-spatial modeling, both of which hinder the reconstruction of fine textures and complex scene structures. To address these issues, we propose LaMamba, a novel RSISR framework that jointly enhances hierarchical feature transmission and frequency-spatial modeling through two key modules. The Layer-aware Feature Integration (LaFI) module adaptively promotes inter-layer feature interaction, effectively preserving shallow spatial cues in deep networks. Meanwhile, the Spatial-Frequency Nonlinear Mapping (SFNM) module adopts a dual-domain fusion strategy by integrating a Gated Dual Feature Interaction (GDFI) and a Magnitude-Phase Adaptive Aggregation (MPAA). GDFI alleviates spatial-domain channel redundancy, while MPAA enhances frequency-domain representation by decoupling magnitude and phase components. The SFNM module then fuses spatial-frequency information via nonlinear mappings. Extensive experiments on six public RSISR benchmarks demonstrate that LaMamba achieves state-of-the-art performance while maintaining computational efficiency, highlighting its practicality for remote sensing applications. The source code is available at https:\/\/github.com\/Lmy-0914\/LaMamba.<\/jats:p>","DOI":"10.3233\/faia251015","type":"book-chapter","created":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:48:55Z","timestamp":1761126535000},"source":"Crossref","is-referenced-by-count":0,"title":["LaMamba: Layer-Aware Mamba with Frequency-Spatial Fusion for Remote Sensing Image Super-Resolution"],"prefix":"10.3233","author":[{"given":"Mingyue","family":"Li","sequence":"first","affiliation":[{"name":"Department of Electronics and Information Engineering, South-Central Minzu University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chengyi","family":"Xiong","sequence":"additional","affiliation":[{"name":"Department of Electronics and Information Engineering, South-Central Minzu University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhirong","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Computer Science, South-Central Minzu University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiayi","family":"Ma","sequence":"additional","affiliation":[{"name":"Electronic Information School, Wuhan University, Wuhan, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2025"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA251015","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T09:48:55Z","timestamp":1761126535000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA251015"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,21]]},"ISBN":["9781643686318"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia251015","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,21]]}}}