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研究生： 邱志祥
Chih-Hsiang Chiu
論文名稱： 自動偵測振鈴現象於復原模糊人臉影像
Automatic Ringing Artifact Detection in Restoring Blurred Face Images
指導教授： 高文忠
Kao, Wen-Chung
學位類別： 碩士
Master
系所名稱： 電機工程學系
Department of Electrical Engineering
論文出版年： 2009
畢業學年度： 97
語文別： 中文
論文頁數： 80
中文關鍵詞： 影像復原 、區域對比增強 、振鈴現象
英文關鍵詞： image restoration, local contrast enhancement, ringing artifacts
論文種類： 學術論文
相關次數： 點閱：190  下載：21 
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    • 利用盲卷積進行復原模糊影像的已經廣泛研究了很長時間，但是一般的解決方法面對任何模糊影像仍然是一個巨大的挑戰。在這篇論文中，我們提出了一種新的人臉模糊影像復原方法，根據溫納濾波和辨識技術。嘗試數種不同的模糊圈半徑用於溫納濾波器和區域對比增強，更進一步加強被復原影像的紋理。我們所提出的系統可以自動確定較好的卷積模糊圈半徑，即是當我們在復原模糊影像時可以避免產生振鈴現象。

    Restoring blurred images by blind deconvolution has been extensively studied for a long time. But a general solution for deblurring any out-of-focus images is still a big challenge. In this paper, we present a new face image restoration approach based on Wiener filter and pattern recognition techniques. By trying several radii of circle of confusion (COC) used in Wiener filter and applying local contrast enhancement to further enhance the textures of deblurred images, the proposed system can automatically determine the best deconvolution radius of COC such that the deblurred image has less ringing artifacts.

    摘　　　　要 i ABSTRACT ii 致 謝 iii 目　　錄 iv 圖目錄 viii 表目錄 xii 第一章 緒論 1 1.1 研究動機 1 1.2 問題描述 2 1.3 點擴散函數 6 1.4 對焦模型 6 1.5 相關研究 9 1.5.1 影像復原相關研究 9 1.5.2 影像品質評估相關研究 24 1.6 本論文提出之方法 31 1.7 論文架構 32 第二章 振鈴現象偵測系統之架構 33 2.1 系統簡介 33 2.2 偵測系統流程 35 第三章 振鈴現象偵測演算法 38 3.1 系統概述 38 3.2 影像的前置處理 39 3.3溫納濾波器 40 3.4色彩空間轉換 42 3.4.1 RGB 42 3.4.2 YCbCr 43 3.5 區域性對比增強 43 3.6 特徵抽取 45 3.6.1 DCT簡介 45 3.6.2 特徵抽取與統計分析 46 3.7 使用支持向量機作為分類核心系統 52 3.7.1 支持向量機簡介 52 3.7.1.1 線性可分離 55 3.7.1.2 線性不可分離 55 3.7.1.3 非線性可分離 56 3.7.2 Ringing Artifacts偵測 59 第四章 實驗結果 62 4.1 模擬模糊影像 62 4.2 人臉資料庫 63 4.3 YALE人臉資料庫B及EXTENDED YALE人臉資料庫B實驗結果 64 4.3.1 每個subset取2張影像之實驗結果 68 4.3.2 每一類取前面七個人的影像之實驗結果 71 4.4 模糊人臉影像復原PSNR比較 73 第五章 結論與未來工作 74 5.1 結論 74 5.2 未來工作 75 參考文獻 76

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