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    題名: A Comparison of Feature-Combination for Example-Based Super Resolution
    作者: 顏淑惠Shwu-Huey Yen
    Jen-Hui Tsao
    and Wan-Ting Liao
    貢獻者: 資訊工程學系暨研究所
    關鍵詞: Super Resolution
    日期: 2014-05-13
    上傳時間: 2015-03-12 19:52:03 (UTC+8)
    摘要: Super resolution (SR) in computer vision is an important task. In this paper, we compared several common used features in image super resolution of example-based algorithms. To combine features, we develop a cascade framework to both solve the problem of deciding weights among features and to improve computation efficiency. Finally, we modify the framework to have an adaptive threshold such that not only the computation load is much reduced but the modified framework is suitable to any query image as well as various image databases.
    關聯: Proceedings of the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)
    顯示於類別:[資訊工程學系暨研究所] 會議論文


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