A Dual Branch Multiscale Stereo Matching Network for High-Resolution Satellite Remote Sensing Images
Accurate disparity estimation of high-resolution satellite remote sensing stereo images serves as a crucial method for generating precise digital surface models. However, the complex intractable regions in satellite images (textureless regions, repeated texture regions, occlusion regions) pose serio...
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IEEE
2025-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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| Online Access: | https://ieeexplore.ieee.org/document/10758818/ |
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| author | Zhenghui Xu Yonghua Jiang Jingxue Wang Yunming Wang |
| author_facet | Zhenghui Xu Yonghua Jiang Jingxue Wang Yunming Wang |
| author_sort | Zhenghui Xu |
| collection | DOAJ |
| description | Accurate disparity estimation of high-resolution satellite remote sensing stereo images serves as a crucial method for generating precise digital surface models. However, the complex intractable regions in satellite images (textureless regions, repeated texture regions, occlusion regions) pose serious challenges for accurate disparity estimation. To enhance the matching accuracy within intractable regions, a dual branch multiscale stereo matching network for high-resolution satellite stereo images is proposed. First, a dual branch feature extraction module is designed, which can perform efficient downsampling. This module can enhance the scene awareness capability of the model, enabling it to extract multiscale feature maps and construct multiscale cost volumes. Then, the cost aggregation process is executed in a coarse-to-fine manner. The method employs a simple hourglass structure and leverages low-scale information to guide the aggregation of high-scale cost volumes. Next, a disparity-channel attention mechanism is proposed for the cost aggregation process to obtain more representative feature information. Finally, a simple disparity refinement module is designed by utilizing both intensity and gradient information of the left image to improve the local details of the disparity map. Experiments are performed separately on the GaoFen-7 and US3D datasets. The experimental results indicate that the proposed method is conducive to improving the matching accuracy within intractable regions of satellite images. The structure of the proposed network is simple, which can effectively reduce the network parameters and realize the lightweight of the model. |
| format | Article |
| id | doaj-art-41646e4d795f4935b533b17f0faf0d56 |
| institution | OA Journals |
| issn | 1939-1404 2151-1535 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj-art-41646e4d795f4935b533b17f0faf0d562025-08-20T02:21:51ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352025-01-011894996410.1109/JSTARS.2024.350284210758818A Dual Branch Multiscale Stereo Matching Network for High-Resolution Satellite Remote Sensing ImagesZhenghui Xu0https://orcid.org/0000-0003-3550-8720Yonghua Jiang1https://orcid.org/0000-0001-5777-4144Jingxue Wang2https://orcid.org/0000-0002-8816-4362Yunming Wang3School of Geomatics, Liaoning Technical University, Fuxin, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaSchool of Automation and Electronic Information, Xiangtan University, Xiangtan, ChinaSchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaAccurate disparity estimation of high-resolution satellite remote sensing stereo images serves as a crucial method for generating precise digital surface models. However, the complex intractable regions in satellite images (textureless regions, repeated texture regions, occlusion regions) pose serious challenges for accurate disparity estimation. To enhance the matching accuracy within intractable regions, a dual branch multiscale stereo matching network for high-resolution satellite stereo images is proposed. First, a dual branch feature extraction module is designed, which can perform efficient downsampling. This module can enhance the scene awareness capability of the model, enabling it to extract multiscale feature maps and construct multiscale cost volumes. Then, the cost aggregation process is executed in a coarse-to-fine manner. The method employs a simple hourglass structure and leverages low-scale information to guide the aggregation of high-scale cost volumes. Next, a disparity-channel attention mechanism is proposed for the cost aggregation process to obtain more representative feature information. Finally, a simple disparity refinement module is designed by utilizing both intensity and gradient information of the left image to improve the local details of the disparity map. Experiments are performed separately on the GaoFen-7 and US3D datasets. The experimental results indicate that the proposed method is conducive to improving the matching accuracy within intractable regions of satellite images. The structure of the proposed network is simple, which can effectively reduce the network parameters and realize the lightweight of the model.https://ieeexplore.ieee.org/document/10758818/Disparity-channel attentiondual branch feature extraction (DBFE)satellite remote sensing stereo imagesstereo matching |
| spellingShingle | Zhenghui Xu Yonghua Jiang Jingxue Wang Yunming Wang A Dual Branch Multiscale Stereo Matching Network for High-Resolution Satellite Remote Sensing Images IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Disparity-channel attention dual branch feature extraction (DBFE) satellite remote sensing stereo images stereo matching |
| title | A Dual Branch Multiscale Stereo Matching Network for High-Resolution Satellite Remote Sensing Images |
| title_full | A Dual Branch Multiscale Stereo Matching Network for High-Resolution Satellite Remote Sensing Images |
| title_fullStr | A Dual Branch Multiscale Stereo Matching Network for High-Resolution Satellite Remote Sensing Images |
| title_full_unstemmed | A Dual Branch Multiscale Stereo Matching Network for High-Resolution Satellite Remote Sensing Images |
| title_short | A Dual Branch Multiscale Stereo Matching Network for High-Resolution Satellite Remote Sensing Images |
| title_sort | dual branch multiscale stereo matching network for high resolution satellite remote sensing images |
| topic | Disparity-channel attention dual branch feature extraction (DBFE) satellite remote sensing stereo images stereo matching |
| url | https://ieeexplore.ieee.org/document/10758818/ |
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