A Novel Method for Infrared and Visible Image Fusion using Filters

Abstract

Image fusion is the process of coalescence of two or more images of the same scene taken from different sensors to produce a composite image with rich details. Due to the progression of infrared (IR) and Visible (VI) image fusion and its ever-growing demands it led to an algorithmic development of image fusion in the last several years. The two modalities have to be integrated altogether with the necessary information to form a single image. In this article, a novel image fusion algorithm has been introduced with the combination of bilateral, Robert filters as method I and moving average, bilateral filter as method II to fuse infrared and visible images. The proposed algorithm follows double - scale decomposition by using average filer and the detail information is obtained by subtracting it from the source image. Smooth and detail weights of the source images are obtained by using the two methods mentioned above. Then a weight based fusion rule is used to amalgamate the source image information into a single image. Performances of both methods are compared both qualitatively and quantitatively. Experimental results provide better results for method I compared to method II.