<p>To extend optical lenses depth-of-field, an efficient method is the multifocus fusion of images. An entirely focused image of the same scene was produced from a collection of partially focused images using the image fusion method (i.e., multifocus fusion of images). In this study, a fusion scheme that combines 2-dimensional variational mode decomposition and selects the value of a pixel by averaging with weights for fusion was adopted. In the proposed framework, a two-dimensional multivariate image is decomposed into intrinsic mode functions via 2-dimensional variational mode decomposition. For the same decomposition level, the respective intrinsic mode functions were updated for pixel fusion via the weighted averaging method to obtain the resulting fused image. The simulations performed on the available datasets were compared with the existing algorithms using eight objective performance parameters as well as subjective performance parameters. From the simulation results, we conclude that the proposed algorithm yields better results than existing schemes. Variations in the alpha and tau parameters of the variational mode decomposition were also simulated to determine their dependency on these parameters. In this study, we implemented the proposed algorithm on two embedded platforms, which performed well. The practical results are also presented.</p>