Fusion of Remote Sensing Images using Signal Decomposition Methods: A Comparative Analysis

Abstract

An efficient method for extending the depth-of-field of optical lenses is multi-focus image fusion, which produces an entirely focused image from a collection of partly focused images of the same scheme. In this paper, fusion schemes namely, Self Fractional Fourier Functions, 2D- Variational mode decomposition, 2D- Variational mode decomposition with fusion rule, Bidimensional multivariate Empirical mode Decomposition, and 2D-Compact Variational mode decomposition are compared for Remote sensing images for fusion. Also, a novel approach is derived and compared with the above-stated algorithms. The simulations are performed on available data sets and compared with the existing algorithms using seventeen objective performance parameters and subjective parameters. The simulation results show that the proposed algorithm gives better results than the existing schemes.