ESMII-Net: An edge-synergy and multidimensional information interaction network for remote sensing change detection
In recent advancements, deep learning-based methods for change detection have demonstrated rapid capabilities to identify alterations across extensive regions, underscoring significant research and application potential in remote sensing change detection. Nonetheless, these methods currently encount...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-05-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843225001542 |
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| author | Yixin Chen Xiaogang Ning Ruiqian Zhang Hanchao Zhang Xiao Huang You He |
| author_facet | Yixin Chen Xiaogang Ning Ruiqian Zhang Hanchao Zhang Xiao Huang You He |
| author_sort | Yixin Chen |
| collection | DOAJ |
| description | In recent advancements, deep learning-based methods for change detection have demonstrated rapid capabilities to identify alterations across extensive regions, underscoring significant research and application potential in remote sensing change detection. Nonetheless, these methods currently encounter limitations in feature extraction, often leading to blurred edges and challenges in identifying small-scale changes. To overcome these challenges, we introduce the Edge-Synergy and Multidimensional Information Interaction Network (ESMII-Net) specifically designed for remote sensing change detection. We achieve feature enhancement through the Multidimensional Information Interaction Fusion Module (MIIFM) and, by integrating the edge aware decoder and the Edge-Synergy Module (ESM), guide the model to acquire effective edge information, thereby improving change detection performance. Furthermore, during the loss function formulation, we have incorporated a Small Object Enhancement Factor (SOEF) to prioritize small object detection. An edge-awareness map is also utilized within the model to accurately delineate change edges and assess their influence on adjacent changed pixels. The efficacy of our model and its innovative components has been validated through experimental results on two public datasets, showcasing improved capabilities in detecting edges and small objects. |
| format | Article |
| id | doaj-art-01994eaa7dad452aad722d9a2ce7f0c7 |
| institution | Kabale University |
| issn | 1569-8432 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj-art-01994eaa7dad452aad722d9a2ce7f0c72025-08-20T03:49:42ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322025-05-0113910450710.1016/j.jag.2025.104507ESMII-Net: An edge-synergy and multidimensional information interaction network for remote sensing change detectionYixin Chen0Xiaogang Ning1Ruiqian Zhang2Hanchao Zhang3Xiao Huang4You He5Institute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping, Beijing 100036, ChinaInstitute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping, Beijing 100036, China; Corresponding author.Institute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping, Beijing 100036, ChinaInstitute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping, Beijing 100036, ChinaDepartment of Environmental Sciences, Emory University, Atlanta, GA 30322, USAInstitute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping, Beijing 100036, ChinaIn recent advancements, deep learning-based methods for change detection have demonstrated rapid capabilities to identify alterations across extensive regions, underscoring significant research and application potential in remote sensing change detection. Nonetheless, these methods currently encounter limitations in feature extraction, often leading to blurred edges and challenges in identifying small-scale changes. To overcome these challenges, we introduce the Edge-Synergy and Multidimensional Information Interaction Network (ESMII-Net) specifically designed for remote sensing change detection. We achieve feature enhancement through the Multidimensional Information Interaction Fusion Module (MIIFM) and, by integrating the edge aware decoder and the Edge-Synergy Module (ESM), guide the model to acquire effective edge information, thereby improving change detection performance. Furthermore, during the loss function formulation, we have incorporated a Small Object Enhancement Factor (SOEF) to prioritize small object detection. An edge-awareness map is also utilized within the model to accurately delineate change edges and assess their influence on adjacent changed pixels. The efficacy of our model and its innovative components has been validated through experimental results on two public datasets, showcasing improved capabilities in detecting edges and small objects.http://www.sciencedirect.com/science/article/pii/S1569843225001542Change DetectionRemote SensingEdge-SynergyMultidimensional Information Interaction |
| spellingShingle | Yixin Chen Xiaogang Ning Ruiqian Zhang Hanchao Zhang Xiao Huang You He ESMII-Net: An edge-synergy and multidimensional information interaction network for remote sensing change detection International Journal of Applied Earth Observations and Geoinformation Change Detection Remote Sensing Edge-Synergy Multidimensional Information Interaction |
| title | ESMII-Net: An edge-synergy and multidimensional information interaction network for remote sensing change detection |
| title_full | ESMII-Net: An edge-synergy and multidimensional information interaction network for remote sensing change detection |
| title_fullStr | ESMII-Net: An edge-synergy and multidimensional information interaction network for remote sensing change detection |
| title_full_unstemmed | ESMII-Net: An edge-synergy and multidimensional information interaction network for remote sensing change detection |
| title_short | ESMII-Net: An edge-synergy and multidimensional information interaction network for remote sensing change detection |
| title_sort | esmii net an edge synergy and multidimensional information interaction network for remote sensing change detection |
| topic | Change Detection Remote Sensing Edge-Synergy Multidimensional Information Interaction |
| url | http://www.sciencedirect.com/science/article/pii/S1569843225001542 |
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