A Multiresolution Image Fusion Based on Principle Component Analysis

A multiresolution image fusion method based on principle component analysis (PCA) is presented. A pairs of registered images are decomposed and of multi-resolution representation by wavelet transform, adaptive fusion weight value of the low frequency wavelet coefficients are resolved using PCA, the high frequency wavelet coefficients are fused by local wavelet energy maximum, then fused images is formed by inverse transforming and combining all wavelet coefficients, the proposed algorithm should keep the information of global structure and significant features from the input images. The experimental results show the proposed procedure work well in the precise feature, visibility and structure information of fused image.