臺灣博碩士論文加值系統

本篇論文提出一個以離散小波轉換為基礎的盲目浮水印技術，將原影像經過小波轉換後得到小波係數依照各頻帶間重要性和關聯性的關係藉由scan order和maximum distance的方式建立我們稱之為選擇樹。每次藉由選擇四顆選擇樹並只量化其中一顆來藏入兩個浮水印位元，此種量化方式會使有嵌入與未被嵌入浮水印的選擇樹之間產生明顯的能量上差異而有助於浮水印的取出，且選擇樹經由scan order和maximum distance的組合將每次嵌入的浮水印位元的資訊分散至不同頻帶且空間上最不相關的位置，使其足夠抵抗一般影像攻擊；以往的研究是取兩顆四元樹來嵌入一個位元的浮水印，因為太多四元樹被量化的結果，造成影像容易失真，浮水印不單單只是考量其強韌性，可以抵抗外在影像處理等攻擊，最重要的是在浮水印嵌入後，與原影像不可失真太多，如何在其中取得一平衡點，是一個值得研究的主題。
本論文中提出一個新的方法來嵌入浮水印，每次取二個浮水印位元並嵌入在選出的四顆選擇樹中的其中一顆，且取出浮水印時不需原始影像和浮水印的輔助，因為被量化的樹減少了，不但可以減少嵌入後影像的失真度，且選擇樹藉由scan order和maximum distance的排列，在經過影像處理等攻擊後，例如，JPEG壓縮、low pass filtering、 cropping等，其取出的浮水印也可以大部份正確的辨識出來，實驗結果證明我們提出的方法為一強韌的浮水印技術。

This thesis proposes a blind watermarking algorithm based on wavelet tree quantization. The wavelet coefficients of the host image are grouped into what we term “ selection trees ” which are created by using the method of maximum distance in scan order of the wavelet trees of two frequency bands; the maximum distance is a non-relative position in the spatial domain of the original image. We choose four selection trees and quantize one tree to embed two watermark bits each time. The quantizing process exhibits a large enough energy difference between the quantized and the unquantized trees; this energy difference can be used for watermark extraction. The method not only reduces the number of quantization trees but also distributing the watermark bits over unrelated wavelet trees via a maximum distance in scan order; this method is more resistant to common image processing attacks. Experimental results show that the proposed method is effective against JPEG compression, low pass filtering, cropping, and scaling.

摘要 I
ABSTRACT II
誌謝 III
LIST OF FIGURES VI
CHAPTER1 INTRODUCTION 1
CHAPTER 2 BACKGROUND OF DIGITAL WATERMARKING 5
2.1 Information Hiding 5
2.1.1 Characteristics of watermarking 7
2.1.2 Watermarking embedding technique 8
2.2 Related work 10
2.2.1 I.J. Cox, J. Kilian, F. T. Leighton, and T. Shamoon,1997 10
2.2.2 G. C. Langelaar and R. L. Langendijk , 2001 13
2.2.3 Y.-S. Kim. O.-H. Kown, and R.-H Park, 1999 16
2.2.4 D. Kundur and D. Hatzinakos, 1998 18
2.2.5 Shin-Hao Wang and Yuan-Pei Lin, 2004 22
2.3 Quad tree 28
2.4 Evaluation of the quality of an image 29
2.5 Watermark Verification 30
CHAPTER 3 THE PROPOSED METHOD 31
3.1 Selection trees by maximum distance 32
3.2 Selection tree quantization 36
3.3 Searching for minimum quantization index 37
3.4 Watermark embedding 39
3.5 Watermark extraction 41
CHAPTER 4 EXPERIMENT RESULTS 47
4.1 Attack test 49
4.2 Experiment Analysis 66
REFERENCES 71

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