A Novel Fast Image Fusion Algorithm Based on Directional Contrast and Weighted Activity

Image fusion is a technique to obtain integrated information from multiple images of the same scene. Because the complementary information of different images is effectively used and the interference of redundant information is reduced, the fused image contains richer and more accurate description of the scene than any of the individual source images. In this paper, a novel fast image fusion algorithm based on directional contrast and weighted activity is proposed. Firstly, lifting wavelet transform is applied to the source images to obtain the wavelet coefficients. Secondly, different fusion strategies are employed in different frequency bands to construct wavelet coefficients of the fused image. Finally, the fused image is obtained by lifting wavelet reconstruction. The experimental results of multi-focus and multi-spectral images show this newly proposed fusion algorithm can obtain good performance with lower computational cost.