Multispectral Multifocus Image Fusion with Guided Steerable Frequency and Improved Saliency

Abstract

Multispectral multifocus image fusion remains a challenging problem for the researchers in the computer vision community. In this paper, we propose a novel solution to the above problem using guided filtering, steerable local frequency and an improved model of saliency. In the first place, promising fusion results are obtained through guided steerable local frequency maps. An accurate saliency map is developed next to further enhance these fusion results. Extensive experimentation on the visual, near infrared and thermal spectra clearly demonstrate the superiority of the proposed approach over some of the recently published works.