Fusion of visible and infrared images via complex function
This work addresses image fusion for applications like surveillance or medical imaging by providing a novel method that improves image quality, though it appears incremental as it builds on existing fusion techniques.
The authors tackled the problem of fusing visible and infrared images by representing them as real and imaginary parts of a complex function, resulting in fused phase images with higher local contrast and quality compared to input images and other fusion methods, as shown by experimental assessments using histograms and entropy.
We propose an algorithm for the fusion of partial images collected from the visual and infrared cameras such that the visual and infrared images are the real and imaginary parts of a complex function. The proposed image fusion algorithm of the complex function is a generalization for the algorithm of conventional image addition in the same way as the addition of complex numbers is the generalization for the addition of real numbers. The proposed algorithm of the complex function is simple in use and non-demanding in computer power. The complex form of the fused image opens a possibility to form the fused image either as the amplitude image or as a phase image, which in turn can be in several forms. We show theoretically that the local contrast of the fused phase images is higher than those of the partial images as well as in comparison with the images obtained by the algorithm of the simple or weighted addition. Experimental image quality assessment of the fused phase images performed using the histograms, entropy shows the higher quality of the phase images in comparison with those of the input partial images as well as those obtained with different fusion methods reported in the literature. Keywords: digital image processing, image fusion, infrared imaging, image quality assessment