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    政大機構典藏 > 資訊學院 > 資訊科學系 > 期刊論文 >  Item 140.119/138324


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    題名: Image Denoising Using Adaptive and Overlapped Average Filtering and Mixed-Pooling Attention Refinement Networks
    作者: 彭彥璁
    Peng, Yan-Tsung
    Lin, Ming-Hao
    Hou, Zhi-Xiang
    Cheng, Kai-Han
    Wu, Chin-Hsien
    貢獻者: 資科系
    關鍵詞: image denoising; overlapped averaging; mixed-pooling attention
    日期: 2021-05
    上傳時間: 2021-12-23 15:41:09 (UTC+8)
    摘要: Cameras are essential parts of portable devices, such as smartphones and tablets. Most people have a smartphone and can take pictures anywhere and anytime to record their lives. However, these pictures captured by cameras may suffer from noise contamination, causing issues for subsequent image analysis, such as image recognition, object tracking, and classification of an object in the image. This paper develops an effective combinational denoising framework based on the proposed Adaptive and Overlapped Average Filtering (AOAF) and Mixed-pooling Attention Refinement Networks (MARNs). First, we apply AOAF to the noisy input image to obtain a preliminarily denoised result, where noisy pixels are removed and recovered. Next, MARNs take the preliminary result as the input and output a refined image where details and edges are better reconstructed. The experimental results demonstrate that our method performs favorably against state-of-the-art denoising methods. 
    關聯: Mathematics, pp.1130
    資料類型: article
    DOI 連結: https://doi.org/10.3390/math9101130
    DOI: 10.3390/math9101130
    顯示於類別:[資訊科學系] 期刊論文

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