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研究生:林孟德
研究生(外文):Meng- De Lin
論文名稱:基於各種色彩空間之彩色量化方法
論文名稱(外文):Digital Color Image Quantization Methods Based on Various Color Spaces
指導教授:曾建誠曾建誠引用關係
指導教授(外文):Chien-Cheng Tseng
學位類別:碩士
校院名稱:國立高雄第一科技大學
系所名稱:電腦與通訊工程所
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:2009
畢業學年度:97
語文別:中文
論文頁數:130
中文關鍵詞:彩色影像量化
外文關鍵詞:Digital Color Image Quantization
相關次數:
  • 被引用被引用:1
  • 點閱點閱:349
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
在本論文中,基於各種色彩空間的色彩量化技術被探討。首先,種種不同的
色彩空間表示被描述,共包括RGB,YCbCr,HSI 和CMY 等空間;然後,三種
量化演算法被陳述,共包括中間值切割法,K-means 演算法和模糊C-means 演算
法;其次峰值信雜比(SNR)被用來評估三種量化演算法在各種色彩空間的量化性
能;最後,使用各種彩色影像來實驗示範三種彩色量化方法的有效性。
In this thesis, color image quantization based on various color spaces are investigated.First, several color space representations are described including RGB, YCbCr , HSI and CMY spaces etc. Then, three color quantization algorithms are presented including Median-Cut algorithm, K-Means algorithm and Fuzzy C-means algorithm. Next, the peak
signal-to-noise ratio (SNR) is used to evaluate the performance of three color quantization algorithms in various color spaces. Finally, experimental results are conducted to demonstrate the effectiveness of three color quantization algorithms by using various images.
中文摘要………………………………………………………………I
英文摘要………………………………………………………………II
致謝…………………………………………………………………III
目錄………………………………………………………………… IV
表目錄…………………………………………………………………V
圖目錄…………………………………………………………………VI
壹、緒論………………………………………………………………1
1.1研究背景與動機……………………………………………………1
1.2研究方法……………………………………………………………2
1.3論文架構……………………………………………………………4
貳、色彩空間介紹………………………………………………………5
2.1前言…………………………………………………………………5
2.2色彩空間……………………………………………………………5
参、色彩空間量化方法………………………………………………17
3.1前言………………………………………………………………17
3.2 Median-Cut Algorithm………………………………………18
3.3 K-Means Algorithm……………………………………………42
3.4 Fuzzy C-means Algorithm……………………………………64
3.4三種方法在各種色彩空間實驗結果比較………………………89
3.5 峰值信號雜訊比………………………………………………102
肆、結論與未來展望………………………………………………109
參考文獻………………………………………………………………111
[1] K.M. Kim, C.S. Lee, E.J. Lee, Y.H. Ha, Color image quantization and dithering method based on human visual system characteristics, J. Imaging Sci. Technol, Vol.40 (6),pp.502-509, 1996.
[2] R. Balasubramanian, J.P. Allebach, A new approach to palette selection for color images, Proc. SPIE: Human Vision Visual Process. Digital Display Ⅲ, Vol.1453,
pp.58-69, 1991.
[3] K.E. Spaulding, L.A. Ray, J.R. Sullivan, Secondary quantization of color images for minimum visual distortion, Proc. SPIE: Human Vision Visual Proc. Digital Display IV,vol.1913, pp.261-269, 1993.
[4] R.S. Gentile, J.P. Allebach, E. Walowit, Quantization of color images based on uniform color spaces, J. Imaging Sci Technol, Vol.16 (1) , pp.12-21, 1990.
[5] Zheru Chi,Hong Yan,Tuan Pham, FUZZY ALGORITHMS : With Applications to Image Processing and Pattern Recognition ,Would Scientific ,1996.
[6] I.Pitas ,DIGITAL IMAGE PROCESSING ALGITHMS AND APPLICATIONS ,JOHN WILLY & SONS ,INC ,2000.
[7] Chen Wei-dong, Ding Wei, An improved median-cut algorithm of color image quantization , Computer Science and Software Engineering, 2008 International Conference on Volume 2, pp.943-946 ,Dec. 2008.
[8] Capelle-Laize, A.-S.; Femandez-Maloigne, C.; Colot, O.; TBM for color image processing: a quantization algorithm , Information Fusion, 2006 9th International
Conference pp:1-7 July 2006.
[9] Filho, Carmelo J.A. Bastos; Mello, Carlos A.B.; Andrade, Julio D.; Falcao, Davi M.A.; Lima, Marilia P.; Santos, Wellington P.; Oliveira, Adriano L.I.; Based on Color Quantization by Genetic Algorithms , Tools with Artificial Intelligence, 2007. ICTAI 2007. 19th IEEE International Conference on Volume 1, pp.488-491 ,Oct 2007.
[10] Yik-Hing Fung; Yuk-Hee Chan; A Technique for Producing Scalable Color-Quantized Images With Error Diffusion , IEEE Transactions on Image Processing, Volume
15, Issue 10, pp.3218 -3224, Oct 2006.
[11] Gibson, S.; Harvey, R.; Morphological color quantization, Computer Vision and Pattern Recognition,2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on Volume 2, pp.II-525 - II-530 vol.2,2001.
[12] Thomas, J.-B.; Tremeau, A.; A Gamut Preserving Color Image Quantization , Image Analysis and Processing Workshops, 2007. ICIAPW 2007. 14th International Conference pp.221- 226.,Sept 2007.
[13] Pujol, A.; Liming Chen; Color quantization for image processing using self information , Information, Communications & Signal Processing, 2007 6th International Conference pp.1- 5.,Dec 2007.
[14] J.L. Bentley, J.H. Friedman, Data structure for range searching, Computing Surveys, vol.11, no.4, pp.397-409, Dec 1979.
[15] P. Heckbert, Color image quantization for frame buffer display, ACMTrans. Computer Graphics (SIGGRAPH) 16 (3), pp.297-307, 1982.
[16] A. Kruger, Median-cut color quantization, Dr. Dobb’s Journal, pp.46-92, September 1994.
[17] A. J. Dekker, “Kohonen neural networks for optimal color quantization, ” Network: Computat. Neural Syst., vol. 5, pp. 351-367,1994.
[18] Y. Deng, B. S. Manjunath and Hyundoo Shin. Color image segmentation. IEEE Computer Society Conference on Computer Vision and Pattern, 2:446-451,1999
[19] M.Gervautz and W. Purgathofer, :A simple method for color quantization : Octree quantization,in Graphics Gems,A.S.Glassner,Ed. New York Academic, pp. 287-293, 1990.
[20] T. Haruki and K. Kikuchi, “Video camera system using fuzzy logic,”IEEE Transactions on Consumer Electronics,Vol.38, No.3 ,pp.624-634, Aug. 1992.
[21] I. S. Hsieh and K. C. Fan, “An adative clustering algorithm for color quantization,”Pattern Recognit. Lett., vol. 21, pp. 337-346, 2000.
[22] Y. W. Lin and S. U. Lee, “On the color image segmentation algorithm based on the thresholding and the fuzzy C-means techniques,” Pattern Recognit., vol. 23, no. 9, pp.935-952, 1990.
[23] M. T. Orchard and C. A. Bouman, “Color quantization of images,” IEEE Tran. on Signal Processing vol. 39, NO 12, pp. 2677-2690, 1991.
[24] N. Papamarkos, Antonis E. Atsalakis, and Charalampos P. Strouthopoulos, “Adaptive Color Reduction,” IEEE Tran. on Systems, Man and Cybernetics-Part B:Cybernetics,
Vol. 32, Feb 2002.
[25] P. Scheunders, “A comparison of clustering algorithms applied to color image quantization,” Pattern Recognit. Lett., vol. 18, pp. 1379-1384, 1997.
[26] J. T. Tou and R. C. Gonazlez, “Pattern Recognition Principles,” reading MA:Addison-Wesley 1974.
[27] L. Velho, J. Gomes, and M. V. R. Sobreiro, “Color image quantization by pairwise clustering,” in Proc. Tenth Brazilian Symp Comput. Graph. Image Process., L. H. de Figueiredo and M. L. Netto, Eds. Campos do Jordao, Spain, pp. 203-210 , 1997.
[28] O. Verevka, “The local K-means algorithm for color image quantization,” M.Sc. dissertation, Univ. Alberta, Edmonton, AB,Canada, 1995.
[29] D. X. Zhong and H. Yan. “Color image segmentation using color space analysis and fuzzy clustering,” IEEE Signal Processing Society Workshop, 2:624-633.
[30] S.C. Pei, Y.S. Lo, Color image compression and limited display using self-organizing kohonen map, IEEE Trans. Circuits Systems Video Technol. 8 (2), pp.191-205, 1998.
[31] R. C. Gonzolez, R. E. Woods, Digital image processing Second Edition, Prentice Hall, 2002.
[32] 蒙以正,2004,數位信號處理-應用MATLAB,旗標出版股份有限公司
[33] 繆紹綱,2005,數位影像處理-活用MATLAB,全華書局
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