Multisource image fusion based on double density Dual-tree Complex Wavelet transform

Double-density Dual-tree Complex Wavelet transform is introduced to image fusion based on multi-resolution, images are decomposed by double-density dual-tree complex wavelet transform with multi-level, multi-direction and shift-invariance and according to characters of low and high frequency coefficients respectively, different combination rules are adopted to fuse images and composite coefficients are reconstructed by double-density dual-tree complex wavelet inverse transform. Some fusion experiments are done by several sets of images with different modalities and objective performance assessments are fulfilled to evaluate fusion results. The experimental results indicate that the proposed approach can significantly outperform the traditional image fusion method based on Laplacian pyramid and discrete wavelet transform.