A differentiable approximation approach to contrast-aware image fusion

We propose a new weight optimization method for image fusion to obtain enhanced images. Given as input a set of images of a static scene captured under different photographic conditions such as exposure time and depth of focus, the algorithm modifies the input images based on visual saliency and then searches for a linear combination of the images that maximizes the total amount of gradient magnitudes. The search is performed by approximating a non-differentiable Lagrangian with the log-sum-exp function and then iteratively updating the closed-form analytical solution until convergence. The simple algorithm has converged fast and has demonstrated significant improvement in image quality over several conventional techniques.