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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/100784

    Title: A Comparison of Feature-Combination for Example-Based Super Resolution
    Authors: 顏淑惠Shwu-Huey Yen
    Jen-Hui Tsao
    and Wan-Ting Liao
    Contributors: 資訊工程學系暨研究所
    Keywords: Super Resolution
    Date: 2014-05-13
    Issue Date: 2015-03-12 19:52:03 (UTC+8)
    Abstract: 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.
    Relation: Proceedings of the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Proceeding

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