Region-based image fusion using a combinatory Chebyshev-ICA method

The aim of this paper is to provide an algorithm for image fusion which combines the techniques of Chebyshev polynomial (CP) approximation and independent component analysis (ICA), based on the regional information of input images. We present a region-based method that combines the merits of both techniques. It utilises segmentation to identify edges, texture and other important features in the input image and subsequently apply the different fusion methods according to regions. The proposed method exhibits better perceptual performance than individual CP and ICA fusion approaches especially in noise corrupted images.