Medical images fusion using parameterized logarithmic image processing model and wavelet sub-band selection schemes

Abstract

A novel wavelet sub-band selection scheme for medical image fusion, based on the Parameterized Logarithmic Image Processing (PLIP) model, is presented in this chapter which takes the characteristics of human visual system (HVS) and the spatial distribution of wavelet coefficients into account. The different fusion schemes are applied for the different frequency sub-bands. The visibility weighted average method is selected for coefficients in low-frequency band and a variance based weighted method is selected for coefficients in high-frequency bands. Subsequently, the fused coefficients are processed with consistency verification to guarantee the homogeneity of the fused image. Computer simulations illustrate that the proposed image fusion algorithms with the PLIP model is superior to some existing fusion methods, and can get satisfactory fusion results. © 2013 Springer Science+Business Media New York.