Statistical Model-based fusion of noisy multi-band images in the wavelet domain

A new method for multimodal image fusion, based on statistical modelling of wavelet coefficients, is proposed in this paper. The algorithm draws from the Weighted Average scheme, but incorporates Laplacian bivariate parent-child statistical dependencies. The interscale dependency is brought in the form of shrinkage functions. The proposed method has been shown to perform very well with noisy datasets, outperforming other conventional methods in terms of fusion quality and noise reduction in the fused output.