Pansharpening approach using Hilbert vibration decomposition

Abstract

In this study, a new approach for pansharpening of multispectral and panchromatic (PAN) images is proposed. The proposed technique is based on recently developed signal decomposition technique known as Hilbert vibration decomposition (HVD). In the proposed method, the histogram equalised PAN image is decomposed into many instantaneous amplitude (IA) and frequency components in the decreasing order of energy using the HVD. The IA of the first component (having highest energy) in the decomposition of the PAN image is used to generate the pansharpened image using appropriate pansharpening model. The tuning factor associated with the pansharpening model is optimised by single-objective particle swarm optimization algorithm. This method is also extended for the hyperspectral images. Experimental results of the proposed technique are compared with existing pansharpening methods in terms of both visual perception and objective metrics. It is observed that the proposed pansharpening scheme has improved spectral and spatial qualities as compared with the existing schemes. The effects of aliasing and misregistration errors in the proposed method are also investigated and it is observed that the proposed method is robust against aliasing and misregistration errors as compared with other existing methods.