A new multi-focus image fusion based on two-dimensional emd and genetic algorithm

A multi-focus image fusion method based on two-dimensional empirical mode decomposition and genetic algorithm is presented in this paper. First, a two-dimensional empirical mode decomposition is applied to the decomposition of source images. High and low frequency of intrinsic mode function component are classified by a T-test. Then low frequency coefficients are fused by improved maximum regional information entropy criterion whereas the high frequency coefficients are amalgamated in different threshold ranges of coefficients by regional correlation. The regional correlation threshold is selected by search of genetic algorithm. Finally, combined results are obtained by inverse two-dimensional empirical mode decomposition transform on fusion coefficients. Simulation results show that the proposed algorithm significantly outperforms traditional image fusion methods that are based on the pixel, region, and wavelet, respectively.