Smoothing of Fused Spectral Consistent Satellite Images

Several widely used methods have been proposed for fusing high resolution panchromatic data and lower resolution multi-channel data. However, many of these methods fail to maintain spectral consistency of the fused high resolution image, which is of high importance to many of the applications based on satellite data. Additionally, most conventional methods are loosely connected to the image forming physics of the satellite image, giving these methods an ad hoc feel. Vesteinsson et al. (2005) proposed a method of fusion of satellite images that is based on the properties of imaging physics in a statistically meaningful way. The fusion method was called spectral consistent panshapen- ing (SC) and it was shown that spectral consistency was a direct consequence of imaging physics and hence guaranteed by the SCP. In this paper exploit this framework and investigate two smoothing methods of the fused image obtain by SCP. The first smoothing method is based on Markov random field (MRF) model, while the second method uses wavelet domain hidden Markov models (HMM) for smoothing of the SCP fused image.