PARAMETER ESTIMATION IN BAYESIAN SUPER-RESOLUTION PANSHARPENING USING CONTOURLETS

In this paper, we consider the problem of parameter estimation on the super resolution and Bayesian methodology for pansharpening using contourlet transform. The used methodology is able to incorporate prior knowledge on the expected characteristics of the multispectral images, include information on the unknown parameters in the form of hyperprior distributions and estimate the unknown parameters together with the high resolution multispectral image. The experimental results show that the proposed method not only enhances the spatial resolution of the pansharpened image, but also preserves the spectral information of the original multispectral image.