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研究生:林宗業
研究生(外文):Zong-Ye Lin
論文名稱:運用四元樹分割技術之逐像素預測的可逆式資訊隱藏
論文名稱(外文):Reversible Data Hiding for Pixel-by-Pixel Prediction Using Quad-tree Segmentation
指導教授:沈肇基沈肇基引用關係李金鳳李金鳳引用關係
指導教授(外文):Jau-Ji ShenChin-Feng Lee
口試委員:黃明祥周永振葉春秀
口試委員(外文):Min-Shiang HwangYung-Chen ChouChun-Hsiu Yeh
口試日期:2022-07-21
學位類別:碩士
校院名稱:國立中興大學
系所名稱:資訊管理學系所
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2022
畢業學年度:110
語文別:中文
論文頁數:62
中文關鍵詞:資訊隱藏可逆式資訊隱藏像素值排序資訊隱藏法四元樹分割技術棋盤式之逐像素嵌入方法
外文關鍵詞:Data HidingReversible Data Hiding (RDH)Pixel Value Ordering (PVO)Quad-tree SegmentationCheckerboard-style Pixel-wise Embedding (CPE)
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近年來網路快速發展,資料的傳送越來越方便,但卻導致資料容易有僞造、篡改、竊取等問題,因此促成了保護數位資料的相關技術快速發展,資訊隱藏技術 (Data Hiding) 成為學者研究的熱門主題。其中的可逆式資訊隱藏技術 (Reversible Data Hiding, RDH) 具有可還原掩護圖像的效果,因此不少學者開始研究 RDH,以便在提取秘密訊息後可恢復圖像的原始內容。
本研究提出了運用四元樹分割技術之逐像素預測的可逆式資料隱藏,為基於像素值排序資訊隱藏法 (Pixel Value Ordering, PVO) 的可逆式資訊隱藏技術。本研究使用了四元樹分割技術來分類掩護圖像的區塊,改善了傳統基於 PVO 的分割方法因複雜區塊過多,無法進行藏入的情況。
針對不同大小的掩護圖像區塊,本研究分別使用不同的方法嵌入秘密訊息。對於大面積的平滑區塊,我們使用了高藏量的方式來藏入;而針對小面積的複雜區塊,我們設計了棋盤式之逐像素嵌入方法 (Checkerboard-style Pixel-wise Embedding, CPE) 來個別檢查每個像素值的複雜度並嵌入訊息。並且本研究方法可以依照使用者想藏入訊息的多寡來調整四元樹分割閾值,達到高藏量或高品質的效果。我們提出此方法主要的目的是最大程度的減少複雜區塊的產生,並且可以依照用戶需求調整四元樹分割閾值。
In recent years, with the rapid development of the Internet, the transmission of data has become more and more convenient. However, it also leads to problems such as forgery or tampering of data. As a result, technologies related to protecting digital data have developed rapidly. Data hiding has become a popular research topic. The reversible data hiding (RDH) technology can completely restore the cover image after message has been extracted, so many scholars began to study RDH, so that the original content of the image can be restored after extracting the secret data.
We proposed reversible data hiding for pixel-by-pixel prediction using quad-tree segmentation, which is RDH technology based on pixel value ordering (PVO). In this study, the quad-tree segmentation technique was used to classify the blocks of the cover image. For large-area smooth blocks and small-area complex blocks, we design different method to embed the data. In addition, this research method can adjust the quad-tree segmentation threshold according to the amount of data that the user wants to embed, to achieve the high embedding capacity or high image quality.
摘要 i
Abstract ii
目錄 iii
表目錄 vi
圖目錄 vii
1. 緒論 1
1.1. 研究背景與動機 1
1.2. 研究目的 6
1.3. 研究架構 7
2. 背景文獻探討 9
2.1. 文獻相關符號定義 9
2.2. 差值擴張法 (Difference Expansion, DE) 10
2.3. 直方圖位移 (Histogram Shifting, HS) 10
2.4. 像素值排序可逆資訊隱藏法 (Pixel Value Ordering, PVO) 11
2.5. 改良的像素排序可逆資訊隱藏法 (Improved Pixel Value Ordering, IPVO) 12
2.6. K 個參數的像素值排序可逆資訊隱藏法 (Pixel Value Ordering-K, PVO-K) 14
2.7. 基於像素的像素值排序法 (Pixel-based Pixel Value Ordering, PPVO) 16
2.8. 星型像素值排序法 (Star-Shaped Pixel Value Ordering, SSPVO) 18
2.9. 重疊像素值排序法 (Overlapping Pixel Value Ordering, OPVO) 19
2.10. 四元樹 (Quad-Tree) 22
3. 研究方法 23
3.1. 方法介紹 23
3.1.1. 四元樹切割 (Quad-Tree Segmentation) 23
3.1.2. 重疊 IPVO (Overlapping Improved Pixel Value Ordering, OIPVO) 27
3.1.3. 四元樹之基於像素的像素值排序法 Quad-PPVO (Quad Pixel-based Pixel Value Ordering) 27
3.1.4. 棋盤式之逐像素嵌入方法 (Checkerboard-style Pixel-wise Embedding, CPE) 28
3.2. 數據嵌入過程 30
3.2.1. 運用四元樹分割技術之逐像素預測資料隱藏嵌入程序 30
3.2.2. 重疊 IPVO (Overlapping Improved Pixel Value Ordering, OIPVO) 方法之嵌入程序 31
3.2.3. 四元樹之基於像素的像素值排序法 Quad-PPVO (Quad Pixel-based Pixel Value Ordering) 之嵌入程序 32
3.2.4. 棋盤式之逐像素嵌入方法 (Checkerboard-style Pixel-wise Embedding, CPE) 之嵌入程序 33
3.3. 數據提取過程 34
3.3.1. 運用四元樹分割技術之逐像素預測的訊息提取與影像還原程序 35
3.3.2. CPE 方法之提取與影像區塊還原程序 36
3.3.3. IPVO 方法之提取與影像區塊還原程序 36
3.3.4. Quad-PPVO 方法之提取與影像區塊還原程序 37
3.3.5. OIPVO 方法之提取與影像區塊還原程序 38
3.4. 秘密訊息嵌入和提取過程之範例 38
3.4.1. OIPVO 嵌入和提取過程之範例 38
3.4.2. Quad-PPVO 嵌入和提取過程之範例 39
3.4.3. IPVO 嵌入和提取過程之範例 41
3.4.4. CPE 嵌入和提取過程之範例 42
4. 實驗結果 44
4.1. 環境說明 44
4.2. 探究本研究方法的區塊分割閾值 (ns_thr) 設置 45
4.3. 探究 CPE 方法的門檻值 (p_thr) 設置 49
4.4. 本研究方法的藏量影像品質之效能分析 53
5. 結論與未來展望 58
5.1. 結論 58
5.2. 未來展望 58
參考文獻 60
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