Correlation Matrix-Based Fusion of Hyperspectral and Multispectral Images
The fusion of the hyperspectral image (HSI) and the multispectral image (MSI) is commonly employed to obtain a high spatial resolution hyperspectral image (HR-HSI); however, existing methods often involve complex feature extraction and optimization steps, resulting in time-consuming fusion processes...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/14/3643 |
| _version_ | 1827731912448278528 |
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| author | Hong Lin Jun Li Yuanxi Peng Tong Zhou Jian Long Jialin Gui |
| author_facet | Hong Lin Jun Li Yuanxi Peng Tong Zhou Jian Long Jialin Gui |
| author_sort | Hong Lin |
| collection | DOAJ |
| description | The fusion of the hyperspectral image (HSI) and the multispectral image (MSI) is commonly employed to obtain a high spatial resolution hyperspectral image (HR-HSI); however, existing methods often involve complex feature extraction and optimization steps, resulting in time-consuming fusion processes. Additionally, these methods typically require parameter adjustments for different datasets. Still, reliable references for parameter adjustment are often unavailable in practical scenarios, leading to subpar fusion results compared to simulated scenarios. To address these challenges, this paper proposes a fusion method based on a correlation matrix. Firstly, we assume the existence of a correlation matrix that effectively correlates the spectral and spatial information of HSI and MSI, enabling fast fusion. Subsequently, we derive a correlation matrix that satisfies the given assumption by deducing the generative relationship among HR-HSI, HSI, and MSI. Finally, we optimize the fused result using the Sylvester equation. We tested our proposed method on two simulated datasets and one real dataset. Experimental results demonstrate that our method outperforms existing state-of-the-art methods. Particularly, in terms of fusion time, our method achieves fusion in less than 0.1 seconds in some cases. This method provides a practical and feasible solution for the fusion of hyperspectral and multispectral images, overcoming the challenges of complex fusion processes and parameter adjustment while ensuring a quick fusion process. |
| first_indexed | 2024-03-11T00:41:24Z |
| format | Article |
| id | doaj.art-ce2a539b76914f808a6262a1ff111234 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T00:41:24Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-ce2a539b76914f808a6262a1ff1112342023-11-18T21:13:40ZengMDPI AGRemote Sensing2072-42922023-07-011514364310.3390/rs15143643Correlation Matrix-Based Fusion of Hyperspectral and Multispectral ImagesHong Lin0Jun Li1Yuanxi Peng2Tong Zhou3Jian Long4Jialin Gui5State Key Laboratory of High-Performance Computing, College of Computer Science and Technology, National University of Defense Technology, Changsha 410073, ChinaCollege of Electronic Science and Technology, National University of Defense Technology, Changsha 410073, ChinaState Key Laboratory of High-Performance Computing, College of Computer Science and Technology, National University of Defense Technology, Changsha 410073, ChinaState Key Laboratory of High-Performance Computing, College of Computer Science and Technology, National University of Defense Technology, Changsha 410073, ChinaState Key Laboratory of High-Performance Computing, College of Computer Science and Technology, National University of Defense Technology, Changsha 410073, ChinaState Key Laboratory of High-Performance Computing, College of Computer Science and Technology, National University of Defense Technology, Changsha 410073, ChinaThe fusion of the hyperspectral image (HSI) and the multispectral image (MSI) is commonly employed to obtain a high spatial resolution hyperspectral image (HR-HSI); however, existing methods often involve complex feature extraction and optimization steps, resulting in time-consuming fusion processes. Additionally, these methods typically require parameter adjustments for different datasets. Still, reliable references for parameter adjustment are often unavailable in practical scenarios, leading to subpar fusion results compared to simulated scenarios. To address these challenges, this paper proposes a fusion method based on a correlation matrix. Firstly, we assume the existence of a correlation matrix that effectively correlates the spectral and spatial information of HSI and MSI, enabling fast fusion. Subsequently, we derive a correlation matrix that satisfies the given assumption by deducing the generative relationship among HR-HSI, HSI, and MSI. Finally, we optimize the fused result using the Sylvester equation. We tested our proposed method on two simulated datasets and one real dataset. Experimental results demonstrate that our method outperforms existing state-of-the-art methods. Particularly, in terms of fusion time, our method achieves fusion in less than 0.1 seconds in some cases. This method provides a practical and feasible solution for the fusion of hyperspectral and multispectral images, overcoming the challenges of complex fusion processes and parameter adjustment while ensuring a quick fusion process.https://www.mdpi.com/2072-4292/15/14/3643hyperspectral imagesuper-resolutionfusioncorrelation matrix |
| spellingShingle | Hong Lin Jun Li Yuanxi Peng Tong Zhou Jian Long Jialin Gui Correlation Matrix-Based Fusion of Hyperspectral and Multispectral Images Remote Sensing hyperspectral image super-resolution fusion correlation matrix |
| title | Correlation Matrix-Based Fusion of Hyperspectral and Multispectral Images |
| title_full | Correlation Matrix-Based Fusion of Hyperspectral and Multispectral Images |
| title_fullStr | Correlation Matrix-Based Fusion of Hyperspectral and Multispectral Images |
| title_full_unstemmed | Correlation Matrix-Based Fusion of Hyperspectral and Multispectral Images |
| title_short | Correlation Matrix-Based Fusion of Hyperspectral and Multispectral Images |
| title_sort | correlation matrix based fusion of hyperspectral and multispectral images |
| topic | hyperspectral image super-resolution fusion correlation matrix |
| url | https://www.mdpi.com/2072-4292/15/14/3643 |
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