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Open AccessArticle

Comparison of Image Fusion Techniques Using Satellite Pour l’Observation de la Terre (SPOT) 6 Satellite Imagery

1
South African National Space Agency, Innovation Hub, Pretoria 0087, Gauteng, South Africa
2
School of Geography, Archaeology and Environmental Studies, University of the Witwatersrand—Johannesburg, Wits 2050, Johannesburg, South Africa
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(5), 1881; https://doi.org/10.3390/app10051881
Received: 27 January 2020 / Revised: 17 February 2020 / Accepted: 18 February 2020 / Published: 10 March 2020
(This article belongs to the Special Issue Advances in Image Processing, Analysis and Recognition Technology)
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. View Full-Text
Keywords: pansharpening; image fusion; image quality; Satellite Pour l’Observation de la Terre (SPOT) 6; spectral consistency; spatial consistency; synthesis pansharpening; image fusion; image quality; Satellite Pour l’Observation de la Terre (SPOT) 6; spectral consistency; spatial consistency; synthesis
MDPI and ACS Style

Mhangara, P.; Mapurisa, W.; Mudau, N. Comparison of Image Fusion Techniques Using Satellite Pour l’Observation de la Terre (SPOT) 6 Satellite Imagery. Appl. Sci. 2020, 10, 1881. https://doi.org/10.3390/app10051881

AMA Style

Mhangara P, Mapurisa W, Mudau N. Comparison of Image Fusion Techniques Using Satellite Pour l’Observation de la Terre (SPOT) 6 Satellite Imagery. Applied Sciences. 2020; 10(5):1881. https://doi.org/10.3390/app10051881

Chicago/Turabian Style

Mhangara, Paidamwoyo; Mapurisa, Willard; Mudau, Naledzani. 2020. "Comparison of Image Fusion Techniques Using Satellite Pour l’Observation de la Terre (SPOT) 6 Satellite Imagery" Appl. Sci. 10, no. 5: 1881. https://doi.org/10.3390/app10051881

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