Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/19677
標題: 植基於影像內插法之適應性可逆式偽裝學技術之研究
A Study of Adaptive Reversible Steganography Based on Image Interpolation
作者: 劉又齊
Liu, Yu-Chi
關鍵字: reversible/lossless steganorgraphic technique;可逆式/無失真偽裝學技術;difference expansion;image interpolation;bilinear interpolation;bicubic interpolation;classification map;差值擴張;影像內插法;雙線性內插法;雙立方內插法;分類圖
出版社: 資訊科學與工程學系所
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Coltuc, J. M. Chassery, “Very Fast Watermarking by Reversible Contrast Mapping,” IEEE Signal Processing Letters, vol. 14, no. 4, pp. 255-258, 2007. [8] J. Fridrich, M. Goljan, and R. Du, “Invertible authentication,” in Proceedings of SPIE, Security Watermarking Multimedia Contents, San Jose, CA, pp. 197-208, Jan. 2001. [9] H. T. Huong Thom , H. V. Canh and T. N. Tien, “Steganalysis for Reversible Data Hiding,” in Proceedings of Database Theory and Application, Korea, Dec. 10-12, pp. 1-8, 2009. [10] S. Jiazheng and S.E. Reichenbach, “Image interpolation by two-dimensional parametric cubic convolution,” IEEE Transactions on Image Processing, vol. 15, no. 7, pp. 1857-1870, July 2006. [11] N.F. Johnson, S. Jajodia, “Exploring steganography: seeing the unseen,” IEEE Computer Magazine, vol. 31, no. 2, pp. 26-34, 1998. [12] L. Kamstra and H. Heijmans, “Reversible data embedding into images using wavelet techniques and sorting,” IEEE Transactions on Image Processing, vol. 14, no. 12, pp. 2082-2090, Dec. 2005. [13] H. J. Kim, V. Sachnev, Y. Q. Shi, J. Nam, and H. G. Choo, “A Novel Difference Expansion Transform for Reversible Data Embedding,” IEEE Transactions on Information Forensics and Security, vol. 3, no. 3, pp. 456-465, Sept. 2008. [14] R.K.-S. Kwan, A.C. Evans and G.B. Pike, “MRI simulation-based evaluation of image-processing and classification methods,” IEEE Transactions on Medical Imaging. vol. 18, no. 11, pp. 1085-1097, Nov 1999. [15] C. C. Lee, H. C. Wu, C. S. Tsai and Y. P. Chu, “Adaptive lossless steganographic scheme with centralized difference expansion,” Pattern recognition, vol. 41, no. 6, pp. 2097-2106, June 2008. [16] S. K. Lee, Y. H. Suh and Y. S. Ho, “Lossless Data Hiding Based on Histogram Modification of Difference Images,” The fifth Pacific-Rim Conference on Multimedia (PCM2004), vol. 3333, pp. 340-347, 2004. [17] C. C. Lin, W. L. Tai and C. C. Chang, “Multilevel Reversible Data Hiding Based on Histogram Modification of Difference Images,” Pattern Recognition, vol. 41, no. 12, pp. 3582-3591, 2008. [18] D. C. Lou, M. C. Hu and J. L. Liu, “Multiple layer data hiding scheme for medical images,” Computer Standards & Interfaces, vol.31, no.2, pp. 329-335, Feb. 2009. [19] Z. Ni, Y. Shi, N. Ansari, and S. Wei, “Reversible data hiding,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 16, no. 3, pp. 354-362, March 2006. [20] J. Suckling, J. Parker, D. Dance, S. Astley, I. Hutt, C. Boggis, I. Ricketts,E. Stamatakis, N. Cerneaz, S. Kok, P. Taylor, D. Betal, and J.Savage, “The mammographic images analysis society digital mammogram database,” Exerpta Medica International Congress Series, vol. 1069, pp. 375-378, 1994. [21] D. M. Thodi, and J. J. Rodriguez, “Expansion embedding techniques for reversible watermarking,” IEEE Transactions on Image Processing, vol. 16, no. 3, pp. 721-730, March 2007. [22] J. Tian, “Reversible data embedding using a difference expansion,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 13, no. 8, pp. 890-896, Aug. 2003. [23] P. Y. Tsai, Y. C. Hu and H. L. Yeh, “Reversible Image Hiding Scheme Using Predictive Coding and Histogram Shifting,” Signal Processing, vol. 89, no. 6, pp. 1129-1143, 2008. [24] H. W. Tseng, and C. C. Chang, “An Extended Difference Expansion Algorithm for Reversible Watermarking,” Image and Vision Computing, vol. 26, no. 8, pp. 1148-1153, Jan. 2008. [25] C. De Vleeschouwer, J. F. Delaigle, and B. Macq, “Circular interpretation of histogram for reversible watermarking,” in Proc. IEEE 4thWorkshop Multimedia Signal Processing, pp. 345-350, Oct. 2001. [26] C. De Vleeschouwer, J. F. Delaigle, and B. Macq, “Circular interpretation of bijective transformations in lossless watermarking for media asset management,” IEEE Transactions on Multimedia, vol. 5, no. 1, pp. 97-105, Mar. 2003. [27] G. Xuan, J. Chen, J. Zhu, Y. Q. Shi, Z. Ni, and W. Su, “Lossless data hiding based on integer wavelet transform,” in Proc. MMSP, St. Thomas, Virgin Islands, pp. 312-315, Dec. 2002. [28] G. Xuan, J. Zhu, J. Chen, Y. Q. Shi, Z. Ni, and W. Su, “Distortionless data hiding based on integer wavelet transform,” IEE Electronics Letters, vol. 38, no. 25, pp. 1646-1648, Dec. 2002. [29] X. Zhang and S. Wang, "Steganography using multiple-base notational system and human vision sensitivity," IEEE Signal Processing Letters, Vol. 12, pp. 67-70, 2005.
摘要: 
可逆式/無失真之偽裝學技術不但允許機密訊息可從偽裝影像中取出,同時更可從中取得無失真的原始影像。它是一個非常重要的技術且漸漸受某些應用上的關注,如真實性的驗證、內容完整度的驗證、珍貴藝術品的保存與醫療或軍事影像上之參照等應用上。近年來的文學中,雖然學者Tian的差值擴張方法是一個突破性的技術,但它依然存著兩個問題:可被考慮的隱藏位置不足及無效率的藏量控制能力。另一方面,學者Lee提出一個適應性可逆式隱藏技術來試圖提升學者Tian的藏量,但在其方法中卻無考慮像素溢位的問題。這樣的結果導致在藏入後,偽裝影像將可能出現惱人的胡椒鹽雜訊。並且,在學者Lee方法中,存在著純黑區塊無法藏入的另一個問題,將導致喪失部份可藏的藏量。
基於影像內插法的特性,本篇博士論文提出三個不同額外資訊需求之適應性可逆式偽裝學技術。在第一個方法中,雙線性內插法的核心被用來改善學者Tian方法中可藏位置的數量,同時偽裝影像的品質也可被維持在一個高的水準之上。另外,我們提出一個簡單化的分類圖方法且結合學者Lee的適應性隱藏規則來解決學者Tian方法中的第二個問題。經由這樣的方式,不但機密訊息能夠適應性的藏入且學者Lee方法中的分類圖大小也可被有效地減少。第二個所提出的方法則採用更強大的雙立方內插法

Reversible/lossless steganography allows the extraction of a secret message and the restoration of the original image without distortion from the stego-image. It is a very important technique that attracts accumulative interests on certain applications, such as authenticity or content integrity, conservation of a valuable art image and reference of medical or military images, etc. Although Tian's difference expansion scheme is regarded as a breakthrough method in recent literature, it suffers from two problems: the embeddable location is considered insufficient and the embedding payload control capability is weak. On the other hand, an adaptive reversible embedding scheme with classification map is proposed by Lee who attempts to increase the embedding payload of Tian's scheme, but the prevention of pixel overflow/underflow is not taken into consideration. This outcome leads to the possible annoying salt-and-pepper noise occurrence on the stego-image after embedding. Moreover, the other issue is the inability to embed the secret message for pure black blocks under Lee's scheme which results in lost partial embedding payload size.
Based on the property of image interpolations, three adaptive reversible steganographic techniques with different sizes of additional information were proposed in this dissertation for solving the above problems. In the first proposed scheme, the kernel of bilinear interpolation is adopted to improve the number of the embeddable locations in Tian's scheme while maintaining the quality of the stego-image the required level. In addition, a simplified classification map is proposed in combination with Lee's adaptive embedding rule to solve the second problem in Tian's scheme so the secret message is able to be embedded adaptively while effectively reducing the classification map of Lee's scheme. The second proposed algorithm adopts a more powerful bicubic interpolation as the pixel prediction to solve the first problem of Tian's scheme. With a powerful bicubic interpolation more embeddable locations can be defined and the quality of generated difference is also taken into consideration. In addition, the statistical adaptive embedding algorithm with lower loading of additional information is proposed to overcome the second problem in Tian's scheme. First, the complexity of the neighboring pixels and the size of the generated difference for the embeddable locations are generalized as the variance conditional using statistics. Combined with the maximum modifiable degree of the predicted value of the embeddable location, the suitable embedding capacity for each embeddable location can then be obtained. Finally, the pixel overflow/underflow problem in Lee's scheme is addressed by, the third proposed scheme, a novel adaptive reversible embedding scheme with a multifunction location map. After obtaining the pixels differences generated by the first proposed scheme, the differences are classified into several sets and then assigned different embedding manners and embedding payloads. After that, the proposed multifunction location map is generated including the two embedding functions: the recognition of the original classification of the embedded difference and the prevention of the pixel underflow/overflow. However, the size of multifunction location map is not greater than Lee's classification map.
In this dissertation, various standard and medical images are adopted as the test images and the experimental results revealed that the three proposed schemes presented better quality stego-image and can carry a larger embedding payload than existing DE-based schemes, such as Tian's, Alattar's and Lee's schemes.
URI: http://hdl.handle.net/11455/19677
其他識別: U0005-0808201000461700
Appears in Collections:資訊科學與工程學系所

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