Fusion and restoration of multifocus image using sparse representation

This paper presents a multifocus image fusion based on sparse representation theory. In the method, first the source images are decomposed by an overcomplete dictionary that contains prototype signal atoms into their corresponding sparse coefficient. Secondly, the corresponding coefficients of the sources images are combined with the choose-max fusion rule. Finally, the fused image is reconstructed from the combined sparse coefficients and the dictionary. The advantage of the proposed method is that it can simultaneously resolve the image restoration and fusion problem by changing the appropriate criterion in the sparse representation algorithm. The proposed method is tested on several multifocus images and compared with Discrete Wavelet Transform based method. The experiment results show the feasibility and effectiveness of the proposed method.