Fusion of Polarization Image Using Bidimensional Empirical Mode Decomposition

Abstract

Empirical mode decomposition (EMD) provides a powerful tool for adaptive multiscale analysis of nonstationary signals. Bidimensional empirical mode decomposition (BEMD) techniques decompose an image into several bidimensional intrinsic mode functions (BIMFs) and a bidimensional residue (BR). Firstly, several polarization images can be decomposed into several BIMFs with multi-scales using BEMD. For the BIMF coefficients, the teager energy-based method is used. For the each BIMF coefficients, the area-based teager energy larger value of information measurement is used to select the better coefficients for fusion. At last the fused image can be obtained by utilizing inverse transform for fused image. Experimental results show that the proposed algorithm gives more satisfactory results than the traditional image fusion algorithms in preserving the edges and texture information.