A differentiable approximation approach to contrast-aware image fusion

Kenji Hara, Kohei Inoue, Kiichi Urahama

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


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.

Original languageEnglish
Article number6781588
Pages (from-to)742-745
Number of pages4
JournalIEEE Signal Processing Letters
Issue number6
Publication statusPublished - Jun 2014

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics


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