A differentiable approximation approach to contrast-aware image fusion

Kenji Hara, Kohei Inoue, Kiichi Urahama

    研究成果: ジャーナルへの寄稿学術誌査読

    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月 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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