Abstract
In remote sensing, image fusion techniques are used to fuse high spatial resolution panchromatic and lower spatial resolution multispectral images that are simultaneously recorded by one sensor. This is done to create high resolution multispectral image datasets (pansharpening). In most cases, these techniques provide very good results, i.e. they retain the high spatial resolution of the panchromatic image and the spectral information from the multispectral image. When applied to multitemporal and/or multisensoral image data, these techniques still create spatially enhanced datasets but usually at the expense of the spectral characteristics. In this study, eight multitemporal remote sensing images are fused with one panchromatic image to test eight different fusion techniques. The fused images are visually and quantitatively analyzed for spectral characteristics preservation and spatial enhancement. Of the employed methods, only the newly developed Ehlers fusion guarantees excellent color preservation and spatial improvement for all dates and sensors.
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Ehlers, M. (2008). Multi-image Fusion in Remote Sensing: Spatial Enhancement vs. Spectral Characteristics Preservation. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2008. Lecture Notes in Computer Science, vol 5359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89646-3_8
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DOI: https://doi.org/10.1007/978-3-540-89646-3_8
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