TY - JOUR
T1 - Fusing Infrared and Visible Images via a First-Order Model
AU - Yang , Wenli
AU - Huang , Zhongyi
AU - Zhu , Wei
JO - Numerical Mathematics: Theory, Methods and Applications
VL - 2
SP - 275
EP - 309
PY - 2024
DA - 2024/05
SN - 17
DO - http://doi.org/10.4208/nmtma.OA-2023-0091 
UR - https://global-sci.org/intro/article_detail/nmtma/23101.html
KW - Image fusion, variational model, augmented Lagrangian methods.
AB - <p style="text-align: justify;">We propose a novel first-order non-convex model for the fusion of infrared
and visible images. It maintains thermal radiation information by ensuring that the
fused image has similar pixel intensities as the infrared image, and it preserves the
appearance information, including the edges and texture of the source images, by
enforcing similar gray gradients and pixel intensities as the visible image. Our model
could effectively reduce the staircase effect and enhance the preservation of sharp
edges. The maximum-minimum principle of the model with Neumann boundary
condition is discussed and the existence of a minimizer of our model in $W^{1,2} (Ω)$ is
also proved. We employ the augmented Lagrangian method (ALM) to design a fast
algorithm to minimize the proposed model and establish the convergence analysis
of the proposed algorithm. Numerical experiments are conducted to showcase the
distinctive features of the model and to provide a comparison with other image
fusion techniques.</p>