English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 49195/83607 (59%)
造訪人次 : 7091830      線上人數 : 51
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/108947


    題名: A 2D Hidden Markov Model for Patch-based Super Resolution
    作者: Hsieh, Chen-Chiung;Chuan, Po-Han
    關鍵詞: Super Resolution;Image Patch;Hidden Markov Model;2D HMM;Viterbi Algorithm
    日期: 2016-03
    上傳時間: 2016-12-20 09:49:18 (UTC+8)
    出版者: 淡江大學出版中心
    摘要: Super resolution is developed to enhance the resolution of images and various kinds of learning based methods were proposed to magnify a single image. This paper presents a 2D hidden Markov model which could do super resolution by using learned image patch pair database. The image patch pairs store the correspondence relation of high-frequency information between low resolution (LR) patches and high resolution (HR) patches. For each input LR patch, the top five similar LR candidate patches in database are searched to construct a 3D cube which can then be modeled by the proposed 2D hidden Markov model (HMM). A novel 2D Viterbi algorithm is developed to find the optimal LR candidate patches that are the most compatible with each other. The resulting super resolution image could be formed by pasting back the corresponding HR patches from patch pair database according to the positions of found optimal LR patches. By objective comparisons of PSNRs/SSIMs and subjective judgment of the generated super resolution images, the proposed 2D HMM method is superior to the traditional interpolation methods and some existing state-of-the-art methods.
    關聯: Journal of Applied Science and Engineering 19(1), pp.95-108
    DOI: 10.6180/jase.2016.19.1.11
    顯示於類別:[淡江理工學刊] 第19卷第1期

    文件中的檔案:

    檔案 大小格式瀏覽次數
    index.html0KbHTML67檢視/開啟

    在機構典藏中所有的資料項目都受到原著作權保護.

    TAIR相關文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回饋