Quality assessment for multitemporal and multisensor image fusion

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Generally, image fusion methods are classified into three levels: pixel level (iconic), feature level (symbolic) and knowledge or decision level. In this paper we focus on iconic techniques for image fusion. There exist a number of established fusion techniques that can be used to merge 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. These techniques, when applied to multitemporal and/or multisensoral image data, still create spatially enhanced datasets but usually at the expense of the spectral consistency. In this study, a series of nine multitemporal multispectral remote sensing images (seven SPOT scenes and one FORMOSAT scene) is fused with one panchromatic Ikonos image. A number of techniques are employed to analyze the quality of the fusion process. The images are visually and quantitatively evaluated for spectral characteristics preservation and for spatial resolution improvement. Overall, the Ehlers fusion which was developed for spectral characteristics preservation for multi-date and multi-sensor fusion showed the best results. It could not only be proven that the Ehlers fusion is superior to all other tested algorithms but also the only one that guarantees an excellent color preservation for all dates and sensors.