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研究生:王彥鈞
研究生(外文):Wang, Yen-Chun
論文名稱:A Study on DWT-Based Digital Image Watermarking
論文名稱(外文):基於離散小波轉換的數位影像浮水印之探討
指導教授:陳朝欽陳朝欽引用關係
指導教授(外文):Chen, Chaur-Chin
學位類別:碩士
校院名稱:國立清華大學
系所名稱:資訊系統與應用研究所
學門:電算機學門
學類:系統設計學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
論文頁數:32
中文關鍵詞:浮水印離散小波轉換
外文關鍵詞:WatermarkingDiscrete Wavelet Transform
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在近幾十年間,由於網路技術與應用的發展,數位多媒體快速地成長。為了預防非法使用者未經允許就能輕易地下載與複製數位多媒體資料,近來數位浮水印在版權保護以及所有權認證中的重要性與日俱增。因為其優秀的多重解析度分析以及空間-頻率局部化的能力,離散小波轉換在數位浮水印中被廣泛地運用。因此,本論文的研究目的在於探討數位浮水印與離散小波轉換之間的關係。本論文提出一個浮水印系統,分別將浮水印嵌入在二階與三階小波轉換的中頻係數中,以調查其對於強健性以及透明度的影響。本論文的實驗使用5/3以及9/7小波轉換以檢視本浮水印系統的成效,實驗結果顯示本浮水印系統在經由各種攻擊實驗包含縮放、平滑處理、加入雜訊、中值濾波、JPEG壓縮以及剪裁處理後能滿足強健性以及透明度。總結而言,本論文的實驗結果顯示使用不同型態的小波轉換對本浮水印系統的表現具有顯著的影響,我們希望本論文能夠促使對於數位浮水印與離散小波轉換之間的關係有更清楚地了解。
During the last few decades, there has been a rapid growth of digital multimedia due to the development of internet technologies and applications. In order to prevent some illegal users who may easily download and copy digital multimedia data without permission, digital watermarking has gathered great importance in the area of copyright protection and owner identification in recent years. Discrete wavelet transform (DWT) has been widely used for digital watermarking due to its excellent multi-resolution analysis and spatial-frequency localization. Thus, the purpose of this thesis attempts to study the relationship between digital watermarking and DWT. This thesis proposes a watermarking scheme that embeds watermarks into the wavelet coefficients of high-low (HL) and low-high (LH) frequency bands of 2-scale and 3-scale wavelet transforms to investigate their effects on robustness and transparency. The experiments of this thesis involves “5/3” and “9/7” wavelet transforms to examine the effects of our watermarking scheme, and the experimental results show that our watermarking scheme satisfies robustness and transparency after a variety of attacks including scaling, smoothing, noise adding, median filtering, JPEG compression, and cropping. In conclusion, the experimental results of this thesis show a distinct effect of using different kinds of wavelet transforms on performance in our watermarking scheme, we are hopeful that this thesis will contribute to a better understanding of the relationship between digital watermarking and DWT.
Chapter 1 Introduction 1
Chapter 2 Discrete Wavelet Transform 5
2.1 Flowchart of Wavelet Transform 5
2.2 Haar Wavelet Transform 6
2.3 Daubechies’ four Wavelet Transform 7
2.4 W5/3 Wavelet Transform 7
2.5 W9/7 Wavelet Transform 9
Chapter 3 A Proposed Watermarking Scheme 12
3.1 Watermark Acquisition 13
3.2 Watermark Embedding 14
3.3 Watermark Extraction 15
3.4 Watermark Detection 15
Chapter 4 Experimental Results 17
4.1 Experiment 1: Scaling 20
4.2 Experiment 2: Smoothing 20
4.3 Experiment 3: Noise Adding 20
4.4 Experiment 4: Median Filtering 20
4.5 Experiment 5: JPEG Compression 20
4.6 Experiment 6: Cropping 20
4.7 Summary 27
Chapter 5 Conclusion and Discussion 30
References 31

[Ahir2011] V.K. Ahire and V. Kshirsagar, “Robust Watermarking Scheme Based
on Discrete Wavelet Transform (DWT) and Discrete Cosine Transform (DCT) for Copyright Protection of Digital Images,” IJCSNS International Journal of Computer Science and Network Security, Vol.11, No.8, 208-213, 2011.
[Chen2002] C.C. Chen, “Watermarking Experiments Based on Wavelet Transforms,” The Proceedings of SPIE: Int'l Conference on Electronic Imaging and Multimedia Technology III, Vol. 4925, 60-68, 2002.
[Chen2006] C.M. Chen, C.C. Chen, and C.C. Chen, “A Comparison of Texture Features Based On SVM and SOM,” International Conference on Pattern Recognition, Vol. 2, 630-633, 2006.
[Cox1997] I.J. Cox, J. Kilian, F.T. Leighton, and T. Shamoon, “Secure spread spectrum watermarking for multimedia,” IEEE Transactions on Image Processing, Vol. 6, No. 12, 1673-1687, 1997.
[Inou1998] H. Inoue, A. Miyazaki, A. Yamamoto, and T. Katsura, “A digital watermark based on the wavelet transform and its robustness on image compression,” IEEE International Conference on Image Processing, Vol. 2, 391-395, 1998.
[Lai2010] C.C Lai and C.C Tsai, “Digital Image Watermarking Using Discrete
Wavelet Transform and Singular Value Decomposition,” IEEE Transactions on Instrumentation and Measurement, Vol. 59, No. 11, 3060-3063, 2010.
[Okag2010] K. Okagaki, K. Takahashi, and H. Ueda, “Robustness Evaluation of Digital Watermarking Based on Discrete Wavelet Transform,” 2010 Sixth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 114-117, 2010.
[Podi2001] C.I. Podilchuk and E.J. Delp, “Digital watermarking: algorithms and applications,” IEEE Signal Processing Magazine, Vol. 18, No. 4, 33-46, 2001.
[Taub2002] D.S. Taubman and M.W. Marcellin, JPEG2000: Image Compression Fundamentals, Standards and Practice, Kluwer Academic Publishers, Boston, 2002.
[Wang1998] H.J. Wang, P.C. Su, and C.C. Jay Kuo, “Wavelet-based digital image watermarking, ” Optics Express, Vol. 3, No. 12, 491-496, 1998.
[Wang2004] S.H. Wang and Y.P. Lin, “Wavelet tree quantization for copyright protection watermarking,” IEEE Transactions on Image Processing, Vol. 13, No 2, 154-165, 2004.
[Web01] http://en.wikipedia.org/wiki/Digital_watermarking, last access on June 5, 2012.
[Web02 http://en.wikipedia.org/wiki/Discrete_wavelet_transform, last access on June 5, 2012.
[Web03] http://en.wikipedia.org/wiki/Haar_wavelet, last access on June 5, 2012.
[Web04] http://en.wikipedia.org/wiki/Arnold’s_cat map, last access on June 5, 2012.
[Wei1998] Z.H. Wei, P. Qin, and Y.Q. Fu, “Perceptual Digital Watermark of Images Using Wavelet Transform,” IEEE Transactions on Consumer Electronics, Vol. 44, No. 4, 1267-1272, 1998.
[Xia1998] X.G. Xia, C.G. Boncelet, and G.R. Arce, “Wavelet transform based watermark for digital images,” Optics Express, Vol. 3, No. 12, 497-507, 1998.

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