Quality Assessment for Multi-sensor Multi-date Image Fusion

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. Usually, image fusion techniques such as intensity-huesaturation (IHS) or Brovey 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. 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 method for image fusion is presented that preserves the spectral characteristics of the multispectral image also for multi-date and multi-sensor data (Ehlers fusion). A series of eight multitemporal multispectral remote sensing images (seven SPOT scenes and one FORMOSAT scene) is fused with one panchromatic Ikonos image. The fused images are visually and quantitatively analyzed for spectral characteristics preservation. These results are then compared to those from a number of standard and advanced fusion techniques. It can 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.