English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 91913/122132 (75%)
Visitors : 25762224      Online Users : 341
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    政大機構典藏 > 理學院 > 資訊科學系 > 期刊論文 >  Item 140.119/129954
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/129954

    Title: Image Haze Removal Using Airlight White Correction, Local Light Filter, and Aerial Perspective Prior
    Authors: 彭彥璁
    Peng, Yan-Tsung;Huang*, S.-C.
    Lu, Zhihui
    Cheng, Fan-Chieh
    Huang, Shih-Chia
    Zheng, Yalun
    Contributors: 資科系
    Keywords: image dehazing;white correction;local light filter;aerial perspective prior
    Date: 2019-03
    Issue Date: 2020-05-26 15:08:42 (UTC+8)
    Abstract: Light is scattered and absorbed when travelling through atmosphere particles, leading to visibility attenuation for images captured, especially in hazy scenes. In addition, hazy images may suffer from color distortion caused by haze or sandstorm, resulting in poor visual quality. In order to effectively enhance visibility and correct possible color casts for such images, we propose a new image dehazing algorithm based on an improved haze optical model, which consists of three modules: Airlight White Correction (AWC), Local Light Filter (LLF), and Aerial Perspective Prior (APP). In the proposed algorithm, the AWC module detects and corrects possible color cast, the LLF module downplays non-hazy bright pixels (e.g. headlight and white objects) for more accurate airlight estimation, and the APP module uses the minimum/maximum channel and their difference for scene transmission estimation. Experimental results demonstrate that the proposed method outperforms other state-of-the-art dehazing methods in three ways: 1) our results have better visual quality, 2) our method performs the best in terms of color restoration, and 3) our method is very efficient at removing haze and color casts.
    Relation: IEEE Transactions on Circuits and Systems for Video Technology, pp.1-1 (early access)
    Data Type: article
    DOI 連結: https://doi.org/10.1109/TCSVT.2019.2902795
    DOI: 10.1109/TCSVT.2019.2902795
    Appears in Collections:[資訊科學系] 期刊論文

    Files in This Item:

    File Description SizeFormat
    409.pdf6077KbAdobe PDF20View/Open

    All items in 政大典藏 are protected by copyright, with all rights reserved.

    社群 sharing

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback