{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T21:36:53Z","timestamp":1774129013396,"version":"3.50.1"},"reference-count":58,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2024,11,10]],"date-time":"2024-11-10T00:00:00Z","timestamp":1731196800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["51675265"],"award-info":[{"award-number":["51675265"]}]},{"name":"National Natural Science Foundation of China","award":["KXKCXJJ202201"],"award-info":[{"award-number":["KXKCXJJ202201"]}]},{"name":"National Natural Science Foundation of China","award":["PAPD"],"award-info":[{"award-number":["PAPD"]}]},{"name":"Interdisciplinary Innovation Fund for Doctoral Students of Nanjing University of Aeronautics and Astronautics","award":["51675265"],"award-info":[{"award-number":["51675265"]}]},{"name":"Interdisciplinary Innovation Fund for Doctoral Students of Nanjing University of Aeronautics and Astronautics","award":["KXKCXJJ202201"],"award-info":[{"award-number":["KXKCXJJ202201"]}]},{"name":"Interdisciplinary Innovation Fund for Doctoral Students of Nanjing University of Aeronautics and Astronautics","award":["PAPD"],"award-info":[{"award-number":["PAPD"]}]},{"name":"Advantage Discipline Construction Project Funding of University in Jiangsu Province","award":["51675265"],"award-info":[{"award-number":["51675265"]}]},{"name":"Advantage Discipline Construction Project Funding of University in Jiangsu Province","award":["KXKCXJJ202201"],"award-info":[{"award-number":["KXKCXJJ202201"]}]},{"name":"Advantage Discipline Construction Project Funding of University in Jiangsu Province","award":["PAPD"],"award-info":[{"award-number":["PAPD"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Remote sensing change detection (RSCD) aims to utilize paired temporal remote sensing images to detect surface changes in the same area. Traditional CNN-based methods are limited by the size of the receptive field, making it difficult to capture the global features of remote sensing images. In contrast, Transformer-based methods address this issue with their powerful modeling capabilities. However, applying the Transformer architecture to image processing introduces a quadratic complexity problem, significantly increasing computational costs. Recently, the Mamba architecture based on state-space models has gained widespread application in the field of RSCD due to its excellent global feature extraction capabilities and linear complexity characteristics. Nevertheless, existing Mamba-based methods lack optimization for complex change areas, making it easy to lose shallow features or local features, which leads to poor performance on challenging detection cases and high-difficulty datasets. In this paper, we propose a Mamba-based RSCD network for difficult cases (DC-Mamba), which effectively improves the model\u2019s detection capability in complex change areas. Specifically, we introduce the edge-feature enhancement (EFE) block and the dual-flow state-space (DFSS) block, which enhance the details of change edges and local features while maintaining the model\u2019s global feature extraction capability. We propose a dynamic loss function to address the issue of sample imbalance, giving more attention to difficult samples during training. Extensive experiments on three change detection datasets demonstrate that our proposed DC-Mamba outperforms existing state-of-the-art methods overall and exhibits significant performance improvements in detecting difficult cases.<\/jats:p>","DOI":"10.3390\/rs16224186","type":"journal-article","created":{"date-parts":[[2024,11,11]],"date-time":"2024-11-11T11:34:11Z","timestamp":1731324851000},"page":"4186","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["DC-Mamba: A Novel Network for Enhanced Remote Sensing Change Detection in Difficult Cases"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-2310-0053","authenticated-orcid":false,"given":"Junyi","family":"Zhang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Mechanics and Control for Aerospace Structures, College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9467-7335","authenticated-orcid":false,"given":"Renwen","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Mechanics and Control for Aerospace Structures, College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China"}]},{"given":"Fei","family":"Liu","sequence":"additional","affiliation":[{"name":"National Key Laboratory on Electromagnetic Environmental Effects and Electro-Optical Engineering, Army Engineering University of PLA, Nanjing 210007, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5607-2180","authenticated-orcid":false,"given":"Hao","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Mechanics and Control for Aerospace Structures, College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China"}]},{"given":"Boyu","family":"Zheng","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Mechanics and Control for Aerospace Structures, College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China"}]},{"given":"Chenyu","family":"Hu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Mechanics and Control for Aerospace Structures, College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5614317","DOI":"10.1109\/TGRS.2024.3483775","article-title":"Bifa: Remote sensing image change detection with bitemporal feature alignment","volume":"62","author":"Zhang","year":"2024","journal-title":"IEEE Trans. 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