Image completion using sample synthesis

[[abstract]]The issue of image completion is well developed in these years. Most of them reconstruct damaged area by referring to the under-repaired images themselves. However, they may fail if damaged portion collapse their structure which is unique and important. We propose to use an external reference image to repair the damaged image and the method provides the following three contributions: (1) an algorithm of fast contour matching is proposed to repair damaged images by referring to external sample images. Critical structural information can be rebuilt which is missing in original damaged area. (2) An algorithm of fragment color transform is proposed to resolve the problem of creating false transform to non-existent color if traditional histogram specification were used. (3) An algorithm of K map threshold weighted synthesis is proposed to resolve the problem of creating false textures caused by non-existence of similar block in original damaged area. Several experiments are executed and the results clearly indicate that defects mentioned above are able to fix more efficiently. Especially, the present method shows good performance for texture accommodation in the joint area. Therefore, it is ideal for the task of completing images with unique structure missing in the damaged area.[[notice]]補正完

[[alternative]]Image completion using sample synthesis

碩士[[abstract]]影像修補技術的應用相當廣泛，大多參考待修補影像的完好部分加以修復，這類方法已經累積了相當豐富的經驗與成果。它們的固有弱點是：如果破損區遮蔽了關鍵的結構，這些方法就無法發揮效用。本論文提出一個基於外部參考樣本的修補技術，它能夠修補關鍵結構被遮蔽的影像。在取得外部參考樣本影像的前提之下，本論文做出三項貢獻：(1) 提出快速的輪廓比對方法，可以從外部樣本影像識別並擷取待修補影像所欠缺的結構資訊。(2) 使用分區式色彩轉換法取代通用的色彩直方分佈匹配法，使參考樣本擷取區的顏色與待修補影像無暇融合，解決了兩者的顏色錯誤匹配問題。(3) 提出 K map 閥值加權合成法，解決了正確區塊不存在於待修補影像而導致錯誤修補的問題。 實驗結果顯示，本論文提出的新技術可以有效地修復缺損結構，對於接縫處的紋理修補難題也獲得相當理想的改善結果，可以做為大範圍缺損影像的修補方法。[[abstract]]The topic of image completion accumulates abundant experience and techniques in decades. Most of them repair damaged portion by referring to their intact surroundings. However, they may often fail if damaged portion collapse their structure which is unique and important. This research provides the following three contributions: (1) An algorithm of fast contour matching is proposed to repair damaged images by referring to external sample images. Critical structural information can be rebuilt which is missing in original damaged area. (2) An algorithm of fragment color transform is proposed to resolve the problem of creating false transform to non-existent color if traditional histogram specification were used. (3) An algorithm of K map threshold weighted synthesis is proposed to resolve the problem of creating false textures caused by non-existence of similar block in original damaged area. Several experiments are executed and the results clearly indicate that defects mentioned above are able to fix more efficiently. Especially, the present method shows good performance for texture accommodation in the joint area. Therefore, it is ideal for the task of completing images with unique structure missing in the damaged area.[[tableofcontents]]目錄 第一章 緒論 1 第二章 相關文獻 4 第三章 研究方法 9 3.1 前處理 11 3.2 Contour matching 12 3.3 Fragment color transform 14 3.4 K map threshold weighted synthesis 18 3.5 Background synthesis 21 第四章 實驗結果與討論 22 第五章 結論與未來研究方向 26 參考文獻 27 附錄：英文論文 29 圖目錄 圖 1-1 傳統影像修補 1 圖 1-2 使用外部參考樣本的影像修補 2 圖 2-1 Criminisi et al. 的實驗結果 5 圖 2-2 使用外部參考影像的影像修補 7 圖 3-1 系統流程圖 10 圖 3-2 前處理 11 圖 3-3 Contour matching 12 圖 3-4 Fragment color transform 16 圖 3-5 α與k的相對關係 16 圖 3-6 與Histogram specification比較 17 圖 3-7 各種符號表示與Geodesic distance 20 圖 3-8 與Weighted synthesis的比較 20 圖 3-9 Background synthesis 21 圖 4-1 BBM與Contour Map時間與Contour total pixel關係圖 22 圖 4-2 不同方法的比較 23 圖 4-3 其它實驗結果 24 圖 4-4 其它實驗結果 25 表目錄 表 1 BBM與Contour Map時間比較 22[[note]]學號: 603420208, 學年度: 10