植基於可回復資訊隱藏上向量量化編碼數位影像之研究

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姓名

黃正達(Cheng-Ta Huang) 查詢紙本館藏

畢業系所

資訊工程學系

論文名稱

植基於可回復資訊隱藏上向量量化編碼數位影像之研究
(The Study of Reversible Data Hiding based on Vector Quantization in Digital Images)

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摘要(中)

資料隱藏(Data Hiding)的技術可以隱藏資料於載體內，來達到通訊保護之目的。因此它提供一個安全方式，使得機密資料可以在公開或開放的管道中傳遞。向量量化編碼(VQ)的資料隱藏技術是影像資料隱藏的其中一種方式，它透過向量量化編碼技術將資料嵌入偽裝的影像中，因此可以避免秘密通訊被第三者攔截。而這類型技術的特點是進行通訊的雙方都需要透過同一本編碼簿，才能正確的對訊息編碼與解碼。向量量化編碼的資料隱藏技術可以是「向量量化編碼可回復」(VQ-Oriented Reversible)，而這種技術可以將偽裝影像還原到原始影像的向量量化的形式。從過去相關文獻來看，向量量化編碼可回復資訊隱藏技術進行的研究可以分成兩部分：以編碼串為輸出的技術以及以影像為輸出的方式。
本論文在這兩方面都提出新的技術來改善向量量化編碼可回復資訊隱藏技術的效能。論文第一部分是針對編碼串為輸出的技術進行研究探討，而本論文所提出的ASCM方法的貢獻在於它比現有的技術具備更高的壓縮率以及更高的藏量。論文第二部分是針對影像為輸出的技術進行研究探討，而本論文在這方面共提出兩種方法：Two-level coding方法與Greedy-USBIRDS方法。其中Two-level coding 有較好的資訊藏量而Greedy-USBIRDS有較好的偽裝影像品質與不錯的資訊藏量。第二部分的貢獻在於，本論文所提出的方法比現有方法有更高的偽裝影像品質，同時也具備高資訊藏量。因此從實驗數據來分析比較本論文的研究成果與其它類似的方法的成果，我們發現本論文的研究成果在編碼串輸出的技術或是影像輸出的技術方面都具有重大的突破，編碼串壓縮率平均可以達到0.439，在影像品質平均可以高達37.27dB，且平均藏量可高達42萬位元。

摘要(英)

Image data hiding is one of the most important techniques for data and communication protection. It embeds data into an image carrier and produce a corresponding stego-image that can then be decoded to obtain the hidden data. Therefore, it provides a secure way to distribute data through a public and open channel. VQ-based data hiding is an image data hiding technique that focuses on the problem of using a shared codebook between the message sender and the receiver to embed data into a cover image and to extract the hidden data from the stego-image. VQ-based data hiding methods can be VQ-oriented reversible, referring to the ability to recover the quantized cover image from the stego-image. VQ-based data hiding methods can be classified into two groups according to their outputs: codestream as the output and image as the output.
This dissertation has made contributions to both groups of the VQ-based data hiding methods. First, this dissertation presents a new method called ASCM that uses codestream as the output. It achieves better compression rate and higher embedding rate than prior similar approaches. Second, this dissertation presents two steganographic methods, the two-level embedding method and the greedy-USBIRDS method, which use images as their outputs. The former method achieves larger embedding capacity than the later method, and the later method achieves better stego-image quality with good embedding capacity. When compared with prior similar methods, both the proposed methods achieve better visual quality and larger embedding capacity on average. The experimental results indicate that, the proposed methods in this dissertation make significant contributions to the area of VQ-based steganographic methods in terms of applicable measures such as the stego-image quality (PSNR: ~37.2dB with embedding capacity: 423,283 bits), the ability to handle complex cover images, and the compression rate (Bit rate: ~0.439).

關鍵字(中)

★ 可回復資訊隱藏
★ 向量量化編碼
★ 邊緣向量量化編碼
★ 偽裝學

關鍵字(英)

★ Reversible data hiding
★ Vector quantization
★ Side-match vector quantization
★ Steganography

論文目次

中文摘要 iv
ABSTRACT v
Table of Contents vii
List of Figures ix
List of Tables xi
List of Algorithms xiii
Chapter 1 Introduction 1
1-1 Research Motivation 1
1-2 Research Backgrounds 3
1-3 VQ-based Image Coding System 3
1-4 Classification of VQ-Based Data-Hiding Methods 6
1-5 Define Some Important Factors to Evaluate the Performance and Test Images in VQ-based Data Hiding Methods. 8
1-6 Contributions of Dissertation 11
1-7 Organization of Dissertation 11
Chapter 2 Literature Reviews 12
2-1 A Lossless Data Embedding Technique by Joint Neighboring Coding 12
2-2 Huffman-Code Strategies to improve MFCVQ-based Reversible Data Hiding 14
2-3 A Scheme of Reversible Information Hiding based on SMVQ 15
2-4 A New Steganographic Scheme based on VQ and SOC 16
2-5 Steganography Scheme based on Side Match Vector Quantization 17
Chapter 3 Data Embedding for Vector Quantization Image Processing on the Basis of Adjoining State-Codebook Mapping 20
3-1 Adjoining State-Codebook Mapping 20
3-2 Data Embedding Algorithm 22
3-3 Data Extraction Algorithm 26
3-4 Experimental results and analyses 28
3-5 Summary 36
Chapter 4 Steganographic Image of VQ-transformation Using Two-Level Encoding with Varied LSB Replacements 37
4-1 VQ Transformation 38
4-2 Two-Level Encoding 39
4-3 Quality and Undetectability Considerations 40
4-4 Image Repairing and Adaptive Quality Control 41
4-5 Secret Data Embedding and Extracting 42
4-6 Experimental Results and Analyses 45
4-7 Summary 53
Chapter 5 Greedy-USBIRDS: A Greedy Steganographic Algorithm Using Secret Bits for Image-Block Repairing Based on Differences under SMVQ 55
5-1 Concept of the Proposed Greedy-USBIRDS Method 55
5-2 Image Repairing Using Secret Bits 56
5-3 Block-Level Embedding and Reversibility Checking 59
5-4 Embedding and Extracting 61
5-5 An Example of the Proposed Greedy-USBIRDS Method 65
5-6 Experimental Results and Analyses 66
5-7 Summary 72
Chapter 6 Conclusions and Future Works 74
Bibliography 77

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指導教授

王尉任(Wei-Jen Wang)

審核日期

2013-7-5

推文