使用差值編碼技術隱藏AMBTC壓縮影像數據以實現高質量影像

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研究生：	李岳霖 Li-Yueh-Lin
論文名稱：	使用差值編碼技術隱藏AMBTC壓縮影像數據以實現高質量影像 AMBTC Compressed Image Data-Hiding for High Image Quality Using Difference Encoding Strategy
指導教授：	張大中 Dah-Chung Chang
口試委員:
學位類別：	碩士 Master
系所名稱：	資訊電機學院 - 通訊工程學系在職專班 Executive Master of Communication Engineering
論文出版年：	2021
畢業學年度：	109
語文別：	中文
論文頁數：	82
中文關鍵詞：	AMBTC 、資訊隱藏、動能絕對值區塊截短碼、PSNR值、差異擴張法
外文關鍵詞：	AMBTC, Data hiding, Absolute moment block truncation coding, PSNR, difference expansion
相關次數：	點閱：21 下載：0
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摘要
在資訊發達的數位時代，隨著網際網路的普及，任何的數位資訊都能透過網際網路廣泛地傳播與散佈，然而享受數位科技帶來的便捷與商機時，有些潛在的問題，比如隱私權及智慧財產權侵犯，著作物的違法複製、歪曲、偽造、割裂或篡改，資料竊取、竊聽與偷窺等，因此，要如何保護數位資料在網路上傳輸時的安全，便成為現今數位時代不容忽視的重要議題。
近年來，資訊安全技術不斷的被學者所提出，例如：密碼學、機密共享及資訊隱藏等，各種資訊安全皆有不同的優缺點。例如，傳送方將數位資料以金鑰加密產生密文，密文透過網路傳送到接收方，再以相同的金鑰做解密，以取得機密資料。且因駭客沒有金鑰可以解密，但駭客可以攔截並破壞機密資料，再將已破壞的機密資料傳送給接收方，如此接收方即使有金鑰也無法還原原始機密。
為了解決這樣的問題，已有眾多學者提出資訊隱藏的概念，當資訊隱藏在嵌入更多的機密數據及數值較大的情況下，本文提出了運用差值編碼實現高品質偽裝影像資訊隱藏方法。該方法使用局部特徵和全域特徵，鄰近機密數據將大多數機密數據轉換為較小的值。反之，一些機密數據被轉換為較大的值。由於嵌入較小的值不會引起嚴重的圖像失真問題，因此，在具有相同嵌入率的情況下，該方法的圖像質量高於以前的方法。
關鍵詞：資訊隱藏、動能絕對值區塊截短碼、PSNR值、差異擴張法。

Abstract
Any digital information can be transmitted widely by internet as Internet become universal. It implies that the digital techniques make that life become convenience. However, there are some potential issues, e.g., private, copyright protection, information copy, tampering, and so on. Therefore, how to protect the digital data transmitted on Internet becomes an important issue.
Recently, information security techniques have been proposed continually, e.g., cryptography, secret sharing, and data hiding. Each information security technique owns different advantages and disadvantages. For example, a sender used key to encrypt digit information as cipher. After transmitting cipher to receiver, `the information can be decrypt to obtain secret data. Although hackers do not have key to decrypted data, he/she can intercept or destroy data, making that receiver cannot obtain correct information.
In order to solve this problem, many scholars proposed the concepts of data hiding. In this paper, a difference encode method is proposed to embed more secret data, where the secret data is large. The proposed method used local and global characteristic to transform most secret data into the smaller values. On contrary, a few secret data are converted into the larger values. Since embedding the smaller value does not invoke serious image distortion, the proposed method has better image quality than the previous method with the same embedding ratio.
Keyword: Data hiding, Absolute moment block truncation coding, PSNR, difference expansion

目錄
第1章    序論    1
1.1 簡介    1
1.2章節架構    3
第2章    傳統數據隱藏及AMBTC資訊隱藏    4
2.1 動能絕對值區塊截短碼(AMBTC)    5
2.2 Malik等學者AMBTC資訊隱藏技術    8
2.2.1 Malik等學者架構及藏入過程    8
2.2.2 Malik等學者機密資訊解碼    10
2.3  Ou和Sun AMBTC資訊隱藏技術    12
2.3.1 Ou和Sun機密資訊解碼    14
2.4 Huang等學者機密資訊藏入及資訊解碼    15
2.5 Yeh等學者AMBTC機密資訊藏入    19
2.5.1 計算Entropy及選擇編碼簿    19
2.5.2 Yeh等學者機密嵌入方法    22
2.5.3 Yeh等學者機密資訊解碼方法    24
第3章    運用差值編碼將機密資訊藏入影像    26
3.1 演算法流程    26
3.2 機密資訊藏入方法    28
3.3 上溢(overflow)、下溢(underflow)    30
3.4 機密資訊解碼流程    31
3.5 機密資訊解碼方法    32
3.6 機密資訊藏入分段影像法    33
第4章    影像模擬與結果分析    35
4.1  灰階測試影像    35
4.1.1 AMBTC壓縮影像畫質    36
4.1.2 用於藏入偽裝影像機密資訊藏入圖    37
4.1.3 改變區塊及各方法比較表    38
4.1.4 曲線圖比較    42
4.1.5 差異圖比較    53
4.2 最大藏量及 區塊驗證    58
4.3 機密資訊藏入分段影像法模擬結果    63
4.4 實驗數據    66
第5章    結論    67
參考文獻    68

 
圖目錄
圖2.1:傳統資訊隱藏    4
圖2.2: AMBTC資訊隱藏    4
圖2.3:原始影像取其中一塊 原始區塊    7
圖2.4:原始區塊經AMBTC壓縮流程    7
圖2.5: Malik等學者機密藏入範例    9
圖2.6: Ou和Sun 資訊隱藏    12
圖2.7:Huang等學者機密嵌入流程圖    16
圖2.8: Huang等學者嵌入範例    17
圖2.9: Yeh等學者方法流程圖    19
圖2.10:機密資訊藏入過程    23
圖2.11: Yeh等學者機密資訊解碼流程    25
圖3.1:所提方法之機密編碼與嵌入流程圖    26
圖3.2:2轉10進制    28
圖3.3:差值相減    28
圖3.4:機密資訊轉換規則    29
圖3.5:機密資訊藏入    29
圖3.6:無法嵌入示例    30
圖3.7:所提方法之機密解碼流程圖    31
圖3.8:機密資訊提取    32
圖3.9:機密資訊藏入分段影像流程圖    33
圖3.10: Lena機密資訊藏入分段影像模擬圖    34
圖4.1: 8張灰階測試影像    35
圖4.2: AMBTC影像品質    36
圖4.3: 機密資訊    37
圖4.4: 本篇Airplane 區塊比較    42
圖4.5: 各方法Airplane 區塊比較    42
圖4.6: 各方法Airplane 區塊比較    43
圖4.7: 各方法Airplane 區塊比較    43
圖4.8: 各方法Airplane 區塊比較    43
圖4.9: 本篇Boat 區塊比較    44
圖4.10: 各方法Boat 區塊比較    44
圖4.11: 各方法Boat 區塊比較    44
圖4.12: 各方法Boat 區塊比較    44
圖4.13: 各方法Boat 區塊比較    45
圖4.14: 本篇Lena 區塊比較    45
圖4.15: 各方法Lena 區塊比較    45
圖4.16: 各方法Lena 區塊比較    45
圖4.17: 各方法Lena 區塊比較    46
圖4.18: 各方法Lena 區塊比較    46
圖4.19: 本篇Mandrill 區塊比較    46
圖4.20: 各方法Mandrill 區塊比較    46
圖4.21: 各方法Mandrill 區塊比較    47
圖4.22: 各方法Mandrill 區塊比較    47
圖4.23: 各方法Mandrill 區塊比較    47
圖4.24: 本篇Peppers 區塊比較    47
圖4.25: 各方法Peppers 區塊比較    48
圖4.26: 各方法Peppers 區塊比較    48
圖4.27: 各方法Peppers 區塊比較    48
圖4.28: 各方法Peppers 區塊比較    48
圖4.29: 本篇Sailboat 區塊比較    49
圖4.30: 各方法Sailboat 區塊比較    49
圖4.31: 各方法Sailboat 區塊比較    49
圖4.32: 各方法Sailboat 區塊比較    49
圖4.33: 各方法Sailboat 區塊比較    50
圖4.34: 本篇X-ray bones 區塊比較    50
圖4.35: 各方法X-ray bones 區塊比較    50
圖4.36: 各方法X-ray bones 區塊比較    50
圖4.37: 各方法X-ray bones 區塊比較    51
圖4.38: 各方法X-ray bones 區塊比較    51
圖4.39: 本篇Splash 區塊比較    51
圖4.40: 各方法Splash 區塊比較    51
圖4.41: 各方法Splash 區塊比較    52
圖4.42: 各方法Splash 區塊比較    52
圖4.43: 各方法Splash 區塊比較    52
圖4.44: 各方法Airplane 區塊差異圖比較    53
圖4.45: 各方法Boat 區塊差異圖比較    54
圖4.46: 各方法Lena 區塊差異圖比較    54
圖4.47: 各方法Mandrill 區塊差異圖比較    55
圖4.48: 各方法Peppers 區塊差異圖比較    55
圖4.49: 各方法Sailboat 區塊差異圖比較    56
圖4.50: 各方法X-ray bones 區塊差異圖比較    56
圖4.51: 各方法Splash 區塊差異圖比較    57
圖4.52:各方法Airplane 區塊比較    59
圖4.53:各方法Boat 區塊比較    59
圖4.54:各方法Lena 區塊比較    59
圖4.55:各方法Mandrill 區塊比較    59
圖4.56:各方法Peppers 區塊比較    60
圖4.57:各方法Sailboat 區塊比較    60
圖4.58:各方法X-ray bones 區塊比較    60
圖4.59:各方法Splash 區塊比較    60
圖4.60: 平滑區塊釋例    61
圖4.61: Lena 區塊機密資訊藏入分段影像比較圖    64
圖4.62: Lena 區塊機密資訊藏入分段影像比較圖    64
圖4.63: Lena 區塊機密資訊藏入分段影像比較圖    64
圖4.64: Lena 區塊機密資訊藏入分段影像比較圖    64
圖4.65:實驗影像    66
圖4.66:本篇1338張資訊藏入統計圖    66

 
表目錄
表2.1: 字典的總資訊量為12.9454，熵為2.1147    20
表2.2: 字典的總資訊量為12.2313，熵為2.2273    20
表2.3: 字典的總資訊量為12.4898，熵為2.1766    21
表2.4: 字典的總資訊量為11.8957，熵為2.2527    21
表4.1: 差值編碼轉換表    37
表4.2: 各方法 區塊比較    38
表4.3: 各方法 區塊比較    39
表4.4: 各方法 區塊比較    40
表4.5: 各方法 區塊比較    40
表4.6: 各方法 區塊比較    58
表4.7: Lena機密資訊藏入分段影像各區塊統計表    63
 

                                

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