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    题名: Image Denoising based on Overlapped and Adaptive Gaussian Smoothing and Convolutional Refinement Networks
    作者: 彭彥璁
    Peng, Yan-Tsung
    Lin, M.-H.
    Tang, C.-L.
    Wu, C.-H.
    贡献者: 資科系
    日期: 2019-09
    上传时间: 2020-03-02 15:23:01 (UTC+8)
    摘要: We propose to use overlapped and adaptive Gaussian smoothing (OAGS) and convolutional refinement networks (CRN) to recover images corrupted by salt-and-pepper noise. First, the OAGS method identifies noise pixels and recover them. Then, CRN further improve and restore the recovered results with sharper and clearer edges. Experimental results demonstrate the proposed OAGS+CRN method significantly outperforms state-of-the-art denoising methods.
    關聯: 2019 IEEE International Symposium on Multimedia (ISM), University of California, Irvine
    数据类型: conference
    DOI 連結: https://doi.org/10.1109/ISM46123.2019.00032
    DOI: 10.1109/ISM46123.2019.00032
    显示于类别:[資訊科學系] 會議論文

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