General shearlet pansharpening method using Bayesian inference

Pansharpening is a technique that fuses the information of a low resolution multispectral image and a high resolution panchromatic image, usually remote sensing images, to produce a high resolution multispectral image. In the literature, this task has been addressed from different points of view being one of the most popular the wavelets and contourlet based algorithms. Recently, the shearlet transform, has been proposed. This transform combines the advantages of the wavelets and contourlet transform, with a more efficient directional information representation. In this paper we propose a new shearlet based pansharpening algorithm that generalizes a number of pansharpening approaches and compare it with contourlet based and shearlet based methods. The performance of the proposed shearlet based method is assessed numerically and visually for synthetic and SPOT images.