Infrared and visual image fusion via iterative quadtree decomposition and Bézier interpolation

Infrared and visual image fusion aims to integrate the salient and complementary features of the infrared image and visual image into one informative image. To achieve this purpose, we have proposed an infrared and visual image fusion method via iterative quadtree decomposition and Bézier interpolation. To be specific, each source image is first decomposed to image patches of multiple sizes in a quadtree structure according to a fixed threshold, then each image patch in the quadtree structure is smoothed by interpolating its four-by-four uniformly distributed pixels with the Bézier interpolation method. With the iteratively smoothed images, multiple scales of bright and dark feature maps of each source image can be gradually extracted from the difference image of every two continuously smoothed images. At last, fusion of the infrared image and visual image can be realized by fusing their multiple scales of bright, dark features and their base images (i.e., final-scale smoothed images). Extensive experiments verify that the proposed method outperforms five state-of-the-art image fusion methods in both qualitative and quantitative evaluations.