Comparison of Image Fusion Techniques Using <i>Satellite Pour l’Observation de la Terre</i> (SPOT) 6 Satellite Imagery
Preservation of spectral and spatial information is an important requirement for most quantitative remote sensing applications. In this study, we use image quality metrics to evaluate the performance of several image fusion techniques to assess the spectral and spatial quality of pansharpened images...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-03-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/5/1881 |
| _version_ | 1818920200835170304 |
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| author | Paidamwoyo Mhangara Willard Mapurisa Naledzani Mudau |
| author_facet | Paidamwoyo Mhangara Willard Mapurisa Naledzani Mudau |
| author_sort | Paidamwoyo Mhangara |
| collection | DOAJ |
| description | Preservation of spectral and spatial information is an important requirement for most quantitative remote sensing applications. In this study, we use image quality metrics to evaluate the performance of several image fusion techniques to assess the spectral and spatial quality of pansharpened images. We evaluated twelve pansharpening algorithms in this study; the Local Mean and Variance Matching (IMVM) algorithm was the best in terms of spectral consistency and synthesis followed by the ratio component substitution (RCS) algorithm. Whereas the IMVM and RCS image fusion techniques showed better results compared to other pansharpening methods, it is pertinent to highlight that our study also showed the credibility of other pansharpening algorithms in terms of spatial and spectral consistency as shown by the high correlation coefficients achieved in all methods. We noted that the algorithms that ranked higher in terms of spectral consistency and synthesis were outperformed by other competing algorithms in terms of spatial consistency. The study, therefore, concludes that the selection of image fusion techniques is driven by the requirements of remote sensing application and a careful trade-off is necessary to account for the impact of scene radiometry, image sharpness, spatial and spectral consistency, and computational overhead. |
| first_indexed | 2024-12-20T01:17:59Z |
| format | Article |
| id | doaj.art-60d5cdfb0007470691e4728433d17677 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-12-20T01:17:59Z |
| publishDate | 2020-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-60d5cdfb0007470691e4728433d176772022-12-21T19:58:31ZengMDPI AGApplied Sciences2076-34172020-03-01105188110.3390/app10051881app10051881Comparison of Image Fusion Techniques Using <i>Satellite Pour l’Observation de la Terre</i> (SPOT) 6 Satellite ImageryPaidamwoyo Mhangara0Willard Mapurisa1Naledzani Mudau2South African National Space Agency, Innovation Hub, Pretoria 0087, Gauteng, South AfricaSouth African National Space Agency, Innovation Hub, Pretoria 0087, Gauteng, South AfricaSouth African National Space Agency, Innovation Hub, Pretoria 0087, Gauteng, South AfricaPreservation of spectral and spatial information is an important requirement for most quantitative remote sensing applications. In this study, we use image quality metrics to evaluate the performance of several image fusion techniques to assess the spectral and spatial quality of pansharpened images. We evaluated twelve pansharpening algorithms in this study; the Local Mean and Variance Matching (IMVM) algorithm was the best in terms of spectral consistency and synthesis followed by the ratio component substitution (RCS) algorithm. Whereas the IMVM and RCS image fusion techniques showed better results compared to other pansharpening methods, it is pertinent to highlight that our study also showed the credibility of other pansharpening algorithms in terms of spatial and spectral consistency as shown by the high correlation coefficients achieved in all methods. We noted that the algorithms that ranked higher in terms of spectral consistency and synthesis were outperformed by other competing algorithms in terms of spatial consistency. The study, therefore, concludes that the selection of image fusion techniques is driven by the requirements of remote sensing application and a careful trade-off is necessary to account for the impact of scene radiometry, image sharpness, spatial and spectral consistency, and computational overhead.https://www.mdpi.com/2076-3417/10/5/1881pansharpeningimage fusionimage quality<i>satellite pour l’observation de la terre</i> (spot) 6spectral consistencyspatial consistencysynthesis |
| spellingShingle | Paidamwoyo Mhangara Willard Mapurisa Naledzani Mudau Comparison of Image Fusion Techniques Using <i>Satellite Pour l’Observation de la Terre</i> (SPOT) 6 Satellite Imagery Applied Sciences pansharpening image fusion image quality <i>satellite pour l’observation de la terre</i> (spot) 6 spectral consistency spatial consistency synthesis |
| title | Comparison of Image Fusion Techniques Using <i>Satellite Pour l’Observation de la Terre</i> (SPOT) 6 Satellite Imagery |
| title_full | Comparison of Image Fusion Techniques Using <i>Satellite Pour l’Observation de la Terre</i> (SPOT) 6 Satellite Imagery |
| title_fullStr | Comparison of Image Fusion Techniques Using <i>Satellite Pour l’Observation de la Terre</i> (SPOT) 6 Satellite Imagery |
| title_full_unstemmed | Comparison of Image Fusion Techniques Using <i>Satellite Pour l’Observation de la Terre</i> (SPOT) 6 Satellite Imagery |
| title_short | Comparison of Image Fusion Techniques Using <i>Satellite Pour l’Observation de la Terre</i> (SPOT) 6 Satellite Imagery |
| title_sort | comparison of image fusion techniques using i satellite pour l observation de la terre i spot 6 satellite imagery |
| topic | pansharpening image fusion image quality <i>satellite pour l’observation de la terre</i> (spot) 6 spectral consistency spatial consistency synthesis |
| url | https://www.mdpi.com/2076-3417/10/5/1881 |
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