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研究生:陳品仁
研究生(外文):Ping-Jen Chen
論文名稱:利用有限狀態機來加速以邊為基礎的反轉半色調演算法
論文名稱(外文):Speed up the Edge–Based Inverse Halftoning Algorithm Using Finite State Machine Model Approach
指導教授:鍾國亮鍾國亮引用關係
指導教授(外文):Kuo-liang Chung
學位類別:碩士
校院名稱:國立臺灣科技大學
系所名稱:資訊工程系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2008
畢業學年度:96
語文別:英文
論文頁數:28
中文關鍵詞:有限狀態機模型半色調影像反轉半色調查表法
外文關鍵詞:Edgesfinite state machine modelhalftone imageinverse halftoning
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在這篇論文中,我們提出了一個新的基於有限狀態機模型之搜尋方法,來加速一個已經存在之基於邊和查表法的反轉半色調影像演算法。在我們的方法中,由三種狀態機所組成的一個二層的有限狀態機,其可以幫助我們在四乘四的搜尋範圍中更有效率的找到J值。 在三十張典型的測試圖片中,實驗結果展現了我們所提出的方法,和已經存在的方法比較後,在平均時間增進的比例上有 53.423% 的執行效率增加。
In this thesis, we propose a new finite state machine model (FSMM)–based search method to speed up the existing edge– and lookup table–based inverse halftoning (ELIH) algorithm significantly which has image quality advantage. In our approach, the two–level FSMM consists of three kinds of finite state machines (FSMs) and it help us to determine the J–value of the current 4 × 4 subedge map efficiently. Under thirty typical testing images, experimental results demonstrated that our proposed FSMM–based ELIH algorithm has 53.423% execution time improvement ratio in average when compared to the currently published ELIH algorithm.
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 The past work: ELIH. . . . . . . . . . . . . . . . . . . . . . . . . . 2
2 Speed up the Edge–Based Inverse Halftoning Algorithm Using Finite
State Machine Model Approach . . . . . . . . . . . . . . . . . . . . . . . 6
2.1 The proposed FSMM–based inverse halftoning algorithm. . . . . . . . 6
2.1.1 Definition 1. . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.1.2 Definition 2. . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.1.3 Definition 3. . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2 Experimental results . . . . . . . . . . . . . . . . . . . . . . . . 17
3 Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
[1] R. A. Ulichney, Digial Halftoning. Cambridge, MA: MIT Press, 1987.
[2] T. D. Kite, N. Damera-Venkata, B. L. Evans and A. C. Bovik, “A fast, high-quality inverse halftoning algorithm for error diffused halftones,” IEEE Trans. Image Processing, vol. 9, pp. 1583–1592, Sept. 2000.
[3] Z. C. Lai and J. Y. Yen, “Inverse error-diffusion using classified vector quantization,” IEEE Trans. Image Processing, vol.7, pp. 1753–1758, Dec. 1998.
[4] M. Y. Shen and C.-C. J. Kuo, “A robust nonlinear filtering approach to inverse halftoning,” J. Visual Communication and Image Representation, vol. 12, pp. 84–95, March 2001.
[5] R. L. Stevenson, “Inverse halftoning via MAP estimation,” IEEE Trans. Image Processing, vol. 6, pp. 574–583, Apr. 1997.
[6] Z. Xiong, M. T. Orchard, and K. Ramchandran, “Inverse halftoning using wavelets,” IEEE Trans. Image Processing, vol. 8, pp. 1479–1482, Oct. 1999.
[7] P. C. Chang, C. S. Yu, and T. H. Lee, “Hybrid LMS–MMS inverse halftoning technique,” IEEE Trans. Image Processing, vol. 10, pp. 95–103, Jan. 2001.
[8] M. Me¸se and P. P. Vaidyanathan, “Look up table (LUT) method for inverse halftoning,” IEEE Trans. Image Processing, vol. 10, pp. 1566–1578, Oct. 2001.
[9] —–, “Tree-Structured method for LUT inverse halftoning and for image halftoning,” IEEE Trans. Image Processing, vol. 11, pp. 644–655, Sept. 2002.
[10] K. L. Chung and S. T. Wu, “Inverse halftoning algorithm using edge-based lookup table approach,” IEEE Trans. on Image Processing, vol. 14, pp. 1583-1589, 2005.
[11] H. R. Lewis, C. H. Papadimitriou, Elements of the theory of computation: Chapter 2., Prentice-Hall, Inc., 1998.
[12] J. Canny, “A computational approach to edge detection,” IEEE Trans. Pattern Anal. and Machine Intelligence, vol. 8, pp. 679–698, Nov. 1986.
[13] [Online]. Available: http://www.systems.caltech.edu/mese/halftone/.
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