Image fusion based on complex contourlet transform and nonnegative matrix factorization

An image fusion method combining complex contourlet transform (CCT) with nonnegative matrix factorization (NMF) is proposed in this paper. After two images are decomposed by CCT, NMF is applied to their highand low-frequency components, respectively, and finally an image is synthesized. Subjective-visual-quality of the image fusion result is compared with those of the image fusion methods based on NMF and the combination of wavelet /contourlet /nonsubsampled contourlet with NMF. The experimental results are evaluated quantitatively, and the running time is also contrasted. It is shown that the proposed image fusion method can gain larger information entropy, standard deviation and mean gradient, which means that it can better integrate featured information from all source images, avoid background noise and promote space clearness in the fusion image effectively.