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    题名: 基於強化學習的影像除雨技術
    Reinforcement-learning-based Image Deraining
    作者: 廖禾豪
    Liao, He-Hao
    贡献者: 彭彥璁
    Peng, Yan-Tsung
    廖禾豪
    Liao, He-Hao
    关键词: 自監督式學習
    強化學習
    影像除雨
    Self-Supervised Learning
    Reinforcement Learning
    Image deraining
    日期: 2024
    上传时间: 2024-03-01 13:41:42 (UTC+8)
    摘要: 戶外拍攝的影像品質經常受到天氣的影響。影響視覺的其中一個因素是影像中的雨紋，它可能阻礙觀察者以及依賴這些影像的電腦視覺應用的視線。本研究旨在通過自監督強化學習（RL）進行影像去雨任務（SRL-Derain）來還原雨天影像。我們通過字典學習從輸入的雨天影像中找到雨紋像素，並使用像素級的強化學習代理進行多次修補(inpainting)操作，逐步去除雨紋。據我們所知，這是首次將自監督強化學習應用於影像去雨的嘗試。來自各種基準影像去雨數據集的實驗結果表明，所提出的方法 SRL-Derain 在與最先進的自監督影像降噪、少量樣本和自監督影像去雨方法相比表現更優。
    The quality of images captured outdoors is often affected by the weather. One factor that interferes with sight is rain, which can obstruct the view of observers and computer vision applications that rely on those images. The work aims to recover rain images by removing rain streaks via Self-supervised Reinforcement Learning (RL) for image deraining (SRL-Derain). We locate rain streak pixels from the input rain image via dictionary learning and use pixel-wise RL agents to take multiple inpainting actions to remove rain progressively. To our best knowledge, this work is the first attempt where self-supervised RL is applied to image draining. Experimental results from various benchmark image-deraining datasets demonstrate that the proposed SRL-Derain exhibits superior performance compared to state-of-the-art self-supervised image denoising, few-shot and self-supervised image deraining methods.
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    描述: 碩士
    國立政治大學
    資訊科學系
    110753115
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0110753115
    数据类型: thesis
    显示于类别:[資訊科學系] 學位論文

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