Object-Level Hybrid Spatiotemporal Fusion: Reaching a Better Tradeoff Among Spectral Accuracy, Spatial Accuracy, and Efficiency
Spatiotemporal fusion (STF) is a cost-effective way to complement the spatiotemporal resolution of multisource images, which has been employed in various applications requiring image sequences. In real-world applications, the spectral accuracy, spatial accuracy, and efficiency of STF play a critical...
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10234600/ |
| _version_ | 1797682007815225344 |
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| author | Dizhou Guo Wenzhong Shi |
| author_facet | Dizhou Guo Wenzhong Shi |
| author_sort | Dizhou Guo |
| collection | DOAJ |
| description | Spatiotemporal fusion (STF) is a cost-effective way to complement the spatiotemporal resolution of multisource images, which has been employed in various applications requiring image sequences. In real-world applications, the spectral accuracy, spatial accuracy, and efficiency of STF play a critical role. Despite this, most STF methods focus on improving spectral accuracy, whereas the challenges of spatial information loss and low efficiency have received limited attention. In addition, the improvements in spectral accuracy, spatial accuracy, and efficiency in STF are contradictory, and existing STF methods cannot balance them well, which limits their reliability and applicability for various STF tasks. To solve the above-mentioned issues, this study proposes an object-level hybrid STF method (OL-HSTFM), which incorporates the efficiency advantage of the object-level fusion strategy, spectral accuracy advantage of the three-step method (Fit-FC), and the spatial accuracy advantage of the spatial and temporal adaptive reflectance fusion model. The performance of OL-HSTFM was compared with two classic STF methods and eight state-of-the-art STF methods at two sites. The experimental results indicate that OL-HSTFM outperforms the other ten methods in overall performance and has excellent efficiency. Furthermore, this study proposes a new metric that can assess the accuracy of both spatial and spectral domains in STF, which provides a more comprehensive and intuitive measurement of the quality of fused images compared to commonly used metrics. |
| first_indexed | 2024-03-11T23:54:13Z |
| format | Article |
| id | doaj.art-8d7aa94e37794477bed43d72eb6303e2 |
| institution | Directory Open Access Journal |
| issn | 2151-1535 |
| language | English |
| last_indexed | 2024-03-11T23:54:13Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj.art-8d7aa94e37794477bed43d72eb6303e22023-09-18T23:00:18ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing2151-15352023-01-01168007802110.1109/JSTARS.2023.331019510234600Object-Level Hybrid Spatiotemporal Fusion: Reaching a Better Tradeoff Among Spectral Accuracy, Spatial Accuracy, and EfficiencyDizhou Guo0https://orcid.org/0000-0001-5325-5080Wenzhong Shi1https://orcid.org/0000-0002-3886-7027Jiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou, ChinaDepartment of Land Surveying and Geo-Informatics, Otto Poon Charitable Foundation Smart Cities Research Institute, The Hong Kong Polytechnic University, Hong Kong, SAR, ChinaSpatiotemporal fusion (STF) is a cost-effective way to complement the spatiotemporal resolution of multisource images, which has been employed in various applications requiring image sequences. In real-world applications, the spectral accuracy, spatial accuracy, and efficiency of STF play a critical role. Despite this, most STF methods focus on improving spectral accuracy, whereas the challenges of spatial information loss and low efficiency have received limited attention. In addition, the improvements in spectral accuracy, spatial accuracy, and efficiency in STF are contradictory, and existing STF methods cannot balance them well, which limits their reliability and applicability for various STF tasks. To solve the above-mentioned issues, this study proposes an object-level hybrid STF method (OL-HSTFM), which incorporates the efficiency advantage of the object-level fusion strategy, spectral accuracy advantage of the three-step method (Fit-FC), and the spatial accuracy advantage of the spatial and temporal adaptive reflectance fusion model. The performance of OL-HSTFM was compared with two classic STF methods and eight state-of-the-art STF methods at two sites. The experimental results indicate that OL-HSTFM outperforms the other ten methods in overall performance and has excellent efficiency. Furthermore, this study proposes a new metric that can assess the accuracy of both spatial and spectral domains in STF, which provides a more comprehensive and intuitive measurement of the quality of fused images compared to commonly used metrics.https://ieeexplore.ieee.org/document/10234600/Object-level processingspatiospectral accuracy metric (SSAM)spatiotemporal fusion (STF) |
| spellingShingle | Dizhou Guo Wenzhong Shi Object-Level Hybrid Spatiotemporal Fusion: Reaching a Better Tradeoff Among Spectral Accuracy, Spatial Accuracy, and Efficiency IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Object-level processing spatiospectral accuracy metric (SSAM) spatiotemporal fusion (STF) |
| title | Object-Level Hybrid Spatiotemporal Fusion: Reaching a Better Tradeoff Among Spectral Accuracy, Spatial Accuracy, and Efficiency |
| title_full | Object-Level Hybrid Spatiotemporal Fusion: Reaching a Better Tradeoff Among Spectral Accuracy, Spatial Accuracy, and Efficiency |
| title_fullStr | Object-Level Hybrid Spatiotemporal Fusion: Reaching a Better Tradeoff Among Spectral Accuracy, Spatial Accuracy, and Efficiency |
| title_full_unstemmed | Object-Level Hybrid Spatiotemporal Fusion: Reaching a Better Tradeoff Among Spectral Accuracy, Spatial Accuracy, and Efficiency |
| title_short | Object-Level Hybrid Spatiotemporal Fusion: Reaching a Better Tradeoff Among Spectral Accuracy, Spatial Accuracy, and Efficiency |
| title_sort | object level hybrid spatiotemporal fusion reaching a better tradeoff among spectral accuracy spatial accuracy and efficiency |
| topic | Object-level processing spatiospectral accuracy metric (SSAM) spatiotemporal fusion (STF) |
| url | https://ieeexplore.ieee.org/document/10234600/ |
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