A differentiable approximation approach to contrast-aware image fusion

Kenji Hara, Kohei Inoue, Kiichi Urahama

研究成果: Contribution to journalArticle査読

9 被引用数 (Scopus)

抄録

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.

本文言語英語
論文番号6781588
ページ(範囲)742-745
ページ数4
ジャーナルIEEE Signal Processing Letters
21
6
DOI
出版ステータス出版済み - 6 2014

All Science Journal Classification (ASJC) codes

  • 信号処理
  • 電子工学および電気工学
  • 応用数学

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