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    题名: Generalization of the Dark Channel Prior for Single Image Restoration
    作者: 彭彥璁
    Peng , Yan-Tsung
    Cao, Keming
    Cosman, Pamela
    贡献者: 資科系
    日期: 2018-06
    上传时间: 2020-03-05 14:40:00 (UTC+8)
    摘要: Images degraded by light scattering and absorption, such as hazy, sandstorm, and underwater images, often suffer color distortion and low contrast because of light traveling through turbid media. In order to enhance and restore such images, we first estimate ambient light using the depth-dependent color change. Then, via calculating the difference between the observed intensity and the ambient light, which we call the scene ambient light differential, scene transmission can be estimated. Additionally, adaptive color correction is incorporated into the image formation model (IFM) for removing color casts while restoring contrast. Experimental results on various degraded images demonstrate the new method outperforms other IFM-based methods subjectively and objectively. Our approach can be interpreted as a generalization of the common dark channel prior (DCP) approach to image restoration, and our method reduces to several DCP variants for different special cases of ambient lighting and turbid medium conditions.
    關聯: IEEE Transactions on Image Processing, Vol.27, No.6, pp.2856 - 2868
    数据类型: article
    DOI 連結: https://doi.org/10.1109/TIP.2018.2813092
    DOI: 10.1109/TIP.2018.2813092
    显示于类别:[資訊科學系] 期刊論文

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