チョウ ゼンシュン   Zhang Shanjun
  張 善俊
   所属   神奈川大学  情報学部 計算機科学科
    神奈川大学大学院  理学研究科 理学専攻(情報科学領域)
   職種   教授
言語種別 英語
発行・発表の年月 2019/01
形態種別 学術雑誌
査読 査読あり
標題 An improved color image defogging algorithm using dark channel model and enhancing saturation
執筆形態 単著
掲載誌名 International Journal for Light and Electron Optics, Optik
掲載区分国外
出版社・発行元 ELSEVIER
巻・号・頁 180(2019),pp.997-1000
担当範囲 research ideas and implementation
概要 Fog is an atmospheric phenomenon that significantly degrades the visibility of outdoor scenes. It
is difficult to lock in and track off criminals clarity in the high-definition surveillance hazy image
and driverless. In our research, we develop dark channel model, re-refined transmission map by
transferring coefficient. Compared with other defogging methods based on single color image
prior, our method is a effectiveness of the proposed defogging algorithm, enhanced the saturation
of defogging image and a higher quality depth map can be obtained of fog removal. In this way, a
clear hazy image is obtained while maintaining the fog removing quality. Moreover, a good
quality defogging image can be validated of fog removal by PSNR and MSE.
DOI https://doi.org/10.1016/j.ijleo.2018.12.020