Color image fusion with extend joint sparse model

In this paper, we present a novel pixel-level color-image fusion method with extension of the joint sparsity model which exploits the inter-correlations among the R, G and B planes. The objective is to achieve the colors more natural for the fused images, compared to individually reconstructing the R, G, B images. This paper also demonstrates an extension of the fusion algorithm to the proper handling of additional Gaussian and impulse noises. Several color multi-focus images are used to test the performances of the proposed method. The results clearly indicate the feasibility of the proposed approach.