本論文主要提出改良式直接二元搜尋區塊截斷編碼技術與多層查詢表半色調浮水印技術兩種應用，其內容大致如下：
第一個方法為改良式直接二元搜尋區塊截斷編碼技術，藉由以直接二元搜尋法之良好的影像品質作為出發點，將其無週期性的特點作為位元平面的產生架構。由於在基於半色調架構之區塊截斷編碼技術當中，使用區塊內的最大值與最小值做為量化色階，會造成脈衝雜訊的問題。因此本方法提出自適應量化色階的方法，加入可調式參數來調整量化色階，並統計不同區塊當中的最佳參數，，進行最佳化參數訓練與調整，期望能改善脈衝雜訊，並取得與區塊效應、假邊現象的平衡，增進其影像品質。由實驗結果可以得知，在高壓縮率的情況下，本論文所提出的方法相較於其他不同的區塊截斷編碼技術有較佳的影像品質。
第二個方法為多層查詢表半色調浮水印技術，本方法主要是植基於一個低計算複雜度的半色調浮水印技術。此外，以雜訊平衡誤差擴散法基於像素的數據隱藏方法將額外的浮水印嵌入至浮水印影像群，用於提高安全性。在編碼端，為了確保輸出影像為半色調影像，因此利用直接二元搜尋法結合不同紋理角度資訊來建立壓縮表。隨後，利用查詢壓縮表的方式將多張浮水印嵌入於單一影像中。在解碼端中，利用最小均方演算法訓練來增加不同維度之嵌入角度紋理特徵之間的差異性。最後，藉由天真貝氏分類器將不同的角度資訊以機率的方式進行分類取得浮水印資訊，解碼後的浮水印能再進一步解出先前嵌入的額外浮水印影像。由實驗結果可以得知，本論文所提出的方法相較於其他不同的半色調浮水印技術，除了有較佳影像品質與解碼率外，還有針對影像大小512x512的最快處理效率8.4毫秒與僅需2MB的壓縮表記憶體儲存空間。因此本論文所提出的方法將能進一步解決半色調影像之安全性問題並提升印刷市場的商業競爭力。

In this thesis, two contributions are presented, including halftoning-based Block Truncation Coding (BTC) using optimized direct binary search and halftoning-based multi-layer lookup table watermarking techniques.
The first proposed method is an improved block truncation coding using optimized direct binary search (ODBSBTC). The images reconstructed by the former halftoning-based BTC schemes suffer from serious impulse noises. To solve this issue, first, the existing regular structures for the bitmap generation are completely modified for yielding aperiodic compressed results. Moreover, an adaptive quantization levels selection strategy is developed, and the parameters are fully optimized. The adaptive quantization levels can be used to provide a balance among false contour, impulsive noise, and blocking artifact. Experimental results demonstrate that the proposed ODBSBTC can achieve excellent image quality, and is superior to that of the former schemes in the literature.
The second proposed method is a multi-layer watermarking of low computational complexity, which can be utilized to improve the security of a halftone image. An additional data hiding technique is also employed to embed multiple watermarks into the watermark of being embedded. At the encoder, the Efficient Direct Binary Search (EDBS) method is employed to generate reference tables to ensure the output is in halftone format. Subsequently, watermarks are embedded by a set of optimized compressive tables with various textural angles for table lookup. At the decoder, the Least-Mean-Square (LMS) metric is considered to increases the differences among those generated phenotypes of the embedding angles, and reduces the required number of dimensions for each angle. Finally, the naive Bayes classifier is employed to collect the possibilities of multi-layer information for classifying the associated angles to extract the embedded watermarks. These decoded watermarks can be further overlapped for retrieving the additional hidden-layer watermarks. Experimental results show that only 8.4 milliseconds is required for embedding a watermark into an image of 512×512 pixels and only 2MB is required to store the proposed compressive reference table.

[1] P. Hamill, “Line printer modification for better grey level pictures,” Computer Graphics and Image Proc., vol. 6, pp. 485-491, 1977.
[2] K. Knowlton and L. Harmon, “Computer-produced greyscales,” Computer Graphics and Image Proc., vol. 1, pp.1-20, 1972.
[3] B. Perry and M. L. Mendelsohn, “Picture generation with a standard line printer,” Comm. of the ACM, 7(5), pp. 311-313, 1964.
[4] J. F. Jarvis and C. Roberts, “A new technique for displaying continuous tone images on a bilevel display,” IEEE Trans. Communication, 24(8), pp. 891-898, Aug. 1976.
[5] R. Ulichney, Digital halftoning, Cambridge, MA: MIT Press, 1987.
[6] R. W. Floyd and L. Steinberg, “An adaptive algorithm for spatial gray scale,” in proc. SID 75 Digest. Society for information Display, pp. 36-37, 1975.
[7] J. F. Jarvis, C. N. Judice, and W. H. Ninke, “A survey of techniques for the display of continuous-tone pictures on bilevel displays,” Comp. Graph. Image Proc., 5(1), pp. 13-40, 1976.
[8] P. Stucki, “MECCA-A multiple-error correcting computation algorithm for bilevel image hardcopy reproduction,” Res. Rep. RZ1060, IBM Res. Lab., Zurich, Switzerland, 1981.
[9] J. N. Shiau and Z. Fan, “A set of easily implementable coefficients in error diffusion with reduced worm artifacts,” SPIE, 2658: 222-225, 1996.
[10] P. Li and J. P. Allebach, “Block interlaced pinwheel error diffusion,” JEI, 14(2), Apr-Jun. 2005.
[11] V. Ostromoukhov, “A simple and efficient error diffusion algorithm,” Computer Graphics (Proceedings of SIGGRAPH 2001), pp. 567-572, 2001.
[12] D. E. Knuth, “Digital halftones by dot diffusion,” ACM Trans. Graph., 6(4), Oct. 1987.
[13] M. Mese and P. P. Vaidyanathan, “Optimized halftoning using dot diffusion and methods for inverse halftoning,” IEEE Trans. Image Processing, 9(4), pp. 691-709, Apr. 2000.
[14] J. M. Guo and Y. F. Liu, “Improved dot diffusion by diffused matrix and class matrix co-optimization,” IEEE Trans. Image Processing, 18(8), pp. 1804-1816, August 2009.
[15] M. Analoui and J. P. Allebach, “Model based halftoning using direct binary search,” Proc. SPIE, vol. 1666, pp. 96-108, 1992.
[16] J. P. Allebach, “FM screen design using DBS algorithm,” in Proc. ICIP, vol. 1, Lausanne, Switzerland, pp. 549-552, 1996.
[17] M. A. Seldowitz, J. P. Allebach, and D. W. Sweeney, “Synthesis of digital holograms by direct binary search,” Appl. Opt., 26(14), pp. 2788-2798, July 1987.
[18] D. J. Lieberman and J. P. Allebach, “Efficient model based halftoning using direct binary search,” IEEE ICIP, pp. 775-778, 1997.
[19] D. J. Lieberman and J. P. Allebach, “A dual interpretation for direct binary search and its implications for tone reproduction and texture quality,” IEEE Trans. Image Processing, 9(11), pp. 1950-1963, 2000.
[20] S. H. Kim and J. P. Allebach, “Impact of HVS models on model-based halftoning,” IEEE Trans. Image Processing, 11(3), pp. 258-269, 2002.
[21] E. J. Delp and O. R. Mitchell, “Image Compression using block truncation coding,” IEEE Trans. Commun. Vol. COMM-27, pp. 1335-1342, Sept. 1979.
[22] D. J. Healy and R. Mitchell, “Digital Video Bandwidth Compression Using Block Truncation Coding,” IEEE Trans. Commun. Vol. COMM-29, No. 12, Dec. 1981.
[23] D. M. Liou, Y. Huang, and and N. Reynolds, “A New Microcomputer Based Imaging System with C3 Technique,” IEEE Region 10 Conference on Coniputer and Coniinunicntion Systems, vol.2, pp. 555-559, Sept. 1990.
[24] J. M. Guo and M. F. Wu, “Improved block truncation coding based on the void-and-cluster dithering approach,” IEEE Trans. Image Processing, vol. 18, no. 1, pp. 211-213, Jan. 2009.
[25] J. M. Guo, “Improved block truncation coding using modified error diffusion,” Electronics Letters, vol. 44, no. 7, pp. 462-464, Mar. 2008.
[26] J. M. Guo and Y. F. Liu “Improved Block Truncation Coding using Optimized Dot Diffusion,” IEEE International Symposium on Circuits and Systems, pp. 2634-2637, May 30-June 2, 2010.
[27] N. Memon and P. W. Wong, “Protecting Digital Media Content,” Commum. of the ACM, vol. 41, pp. 35-43, July 1998.
[28] 潘正祥、張真誠、林詠章，挑戰影像處理：數位浮水印技術，滄海書局，台北，第10-12頁 (2007)。
[29] J. M. Guo and Y. F. Liu, “Joint Compression Watermarking Scheme Using Majority-Parity Guidance and Halftoning-Based Block Truncation Coding,” IEEE Trans. Image Processing, vol. 19, no. 8, Aug. 2010.
[30] J. M. Guo, C. C. Su, Y. F. Liu, H. Lee, and J. D. Lee, “Oriented modulation for watermarking in direct binary search halftone images,” IEEE Trans. Image Processing, vol. 21, no. 9, Sep 2012.
[31] J. R. Goldschneider, E. A. Riskin, and P. W. Wong, “Embedded color error diffusion,” in Proc. IEEE int. Conf. Image processing, vol. 1, pp.565-568, 1996.
[32] Z. Baharav and D. Shaked, “Watermarking of dither halftoned images,” IS&T/SPIE International Conference on Security and Watermarking of Multimedia Content 3657, pp. 307-316, May 1999.
[33] M. S. Fu and O. C. Au, “Hiding data in halftone image using modified data hiding error diffusion,” Proc. SPIE Conf. Visual Communication and Image Processing, vol. 4067, pp. 1671-1680, May 2000.
[34] D. Kacker and J. P. Allebach, “Joint halftoning and watermarking,” IEEE Trans. Signal Processing, vol. 51, no. 4, pp. 1054-1068, April 2003.
[35] G. Sharma and S. G. Wang, “Show-through watermarking of duplex printed documents,” SPIE International Conference on Security, Steganography, and Watermarking of Multimedia Contents VI, vol. 5306, San Jose, pp. 19-22, Jan. 2004.
[36] K. T. Knox, “Digital watermarking using stochastic screen patterns,” U.S. Patent 5734752, 2000.
[37] M. S. Fu and O. C. Au, “Data hiding in halftone images by stochastic error diffusion,” IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 1965-1968, May 2000.
[38] S. C. Pei, and J. M. Guo, ‘‘Hybrid Pixel-Based Data Hiding and Block-Based Watermarking for Error-Diffused Halftone Images,’’ IEEE Trans. Circuits and Systems for Video Technology, vol. 13, no. 8, Aug. 2003.
[39] J. M. Guo, “A new model-based digital halftoning and data hiding designed with LMS optimization,” IEEE Trans. on Multimedia, vol. 9, no. 4, pp. 687-700, June 2007.
[40] J. M. Guo and Y. F. Liu, “Hiding multitone watermarks in halftone images,” IEEE Multimedia, vol. 17, pp. 34-43, January 2010.
[41] B. Widrow and M. E. Hoff, “Adaptive switch circuits,” IRE Western Electric Shhow and Convention Recode, part 4, pp. 96-104, 1960.
[42] P. C. Chang, C. S. Yu and T. H. Lee, “Hybrid LMS-MMSE inverse halftoning technique,” IEEE Trans. On Image Processing, vol. 10, no. 1, pp. 95-103, Jan. 2001.
[43] S. Kirkpatrick et al., “Optimization by simulated annealing,” Science 220, pp. 671-680, 1983.
[44] J. H. Holland, Adaptation in Natural and Artificial Systems. University of Michigan Press: Ann Arbor, MI, 1975.
[45] M. Mitchell, An introduction to genetic algorithm, Cambridge, MA: MIT Press, 1996.
[46] Image Database 1: http://msp.ee.ntust.edu.tw/public%20file/GHLai/ImageSet.rar
[47] Z. Wang, E. P. Simoncelli, and A. C. Bovik, “Multi-scale structural similarity for image quality assessment,” in Proc. IEEE Asilomar Conf. Signals, Syst., Comput., Pacific Grove, CA, Nov. 2003, pp. 1398-1402.
[48] Image Database 2: http://msp.ee.ntust.edu.tw/public%20file/GHLai/Database.rar
[49] J. Sullivan, L. Ray, and R. Miller, “Design of minimum visual modulation halftone patterns,” IEEE Trans. on Systems, Man, and Cybernetics, vol. 21, no. 1, Jan/Feb 1991.
[50] Y. F. Liu, J. M. Guo, and J. D. Lee, “Halftone image classification using LMS algorithm and Naive Bayes,” IEEE Trans. Image Processing, vol. 20, no. 10, Oct 2011.
[51] S. C. Pei, J. M. Guo, and H. Lee, “Novel robust watermarking technique in dithering halftone images,” IEEE Signal Processing Letters, vol. 12, no. 4, pp. 333-336, April 2005.
[52] J. M. Guo, and Y. F. Liu, ‘‘Halftone-Image Security Improving Using Overall Minimal-Error Searching,’’ IEEE Trans. Image Processing, vol. 20, no. 10, Oct. 2011.