Hyperspectral pansharpening using QNR optimization constraint

Abstract

This paper presents a method for pansharpening of low resolution Hyperspectral (HS) images. The proposed method is based upon the optimization of both the spectral and spatial quality criteria of the QNR quality assessment index. The simultaneous optimization of the spectral and spatial quality constraints is obtained by means of the Pareto solutions, obtained by making use of an evolutionary algorithm. A selection criteria is defined to select a single solution from among the Pareto solutions and the results obtained show both quantitative and qualitative improvement over the results obtained by some existing pansharpening methods.