Fractional order variational pan-sharpening

Abstract

In this paper, we propose a new fractional order variational method for pan-sharpening, which aims to obtain a high resolution multi-spectral (MS) image from a low resolution MS image and a high resolution panchromatic (PAN) image. On one hand, we use the data generative constraint for preserving the spectral information. More specifically, on the other hand, we exploit the fractional order gradient feature consistence between the high resolution MS image and PAN image for preserving the spatial information. Based on these assumptions, a new fractional order variational model is proposed and an efficient algorithm is designed to solve the proposed model. Experimental results show that the proposed method outperforms various well-known pan-sharpening methods in terms of higher spatial and spectral qualities.