A general framework for component substitution image fusion: An implementation using the fast image fusion method
Many image fusion algorithms have been developed while more algorithms are being developed to improve the ability of preserving spectral information. Starting from the analysis of component substitution (COS) image fusion technique, a novel general component substitution (GCOS) image fusion framework is proposed, which could be used in three aspects: (1) comparative analysis to existing algorithms, (2) providing a fast technique for current COS fusion methods, and (3) guiding the development of the new COS algorithm. A demonstrative implementation of GCOS is provided, which can employ radiometric properties of sensors in the process of image fusion. An experiment based on degraded IKONOS images was carried out to demonstrate the effectiveness of the method, and the fusion image processed through the proposed method shows a higher correlation coefficient (CC) and a universal image quality index (UIQI), and a lower relative difference (RD) with the reference image in comparison to those yielded through GramSchmidt (GS) spectral sharpening, principal component analysis (PCA), smoothing filter-based intensity modulation (SFIM) and additive wavelet transform (AWT) methods, and provides more reasonable spatial details by visual validation. Validation of the proposed algorithm proved the ability of the proposed GCOS framework.
image fusion algorithm remote sensing spectral response function