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    政大機構典藏 > 理學院 > 資訊科學系 > 會議論文 >  Item 140.119/129021
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/129021

    Title: Image Denoising based on Overlapped and Adaptive Gaussian Smoothing and Convolutional Refinement Networks
    Authors: 彭彥璁
    Peng, Yan-Tsung
    Lin, M.-H.
    Tang, C.-L.
    Wu, C.-H.
    Contributors: 資科系
    Date: 2019-09
    Issue Date: 2020-03-02 15:23:01 (UTC+8)
    Abstract: 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.
    Relation: 2019 IEEE International Symposium on Multimedia (ISM), University of California, Irvine
    Data Type: conference
    DOI 連結: https://doi.org/10.1109/ISM46123.2019.00032
    DOI: 10.1109/ISM46123.2019.00032
    Appears in Collections:[資訊科學系] 會議論文

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