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研究生:陳勝憶
研究生(外文):Sheng-Yi Chen
論文名稱:結合分頻,碎形與量化之影像壓縮
論文名稱(外文):Hybrid Fractal Image Compression and Vector Quantization
指導教授:許舜斌
指導教授(外文):Shuen-Pin Hsu
學位類別:碩士
校院名稱:國立暨南國際大學
系所名稱:電機工程學系
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:2005
畢業學年度:93
語文別:中文
論文頁數:52
中文關鍵詞:小波轉換碎形向量量化資料壓縮
外文關鍵詞:WaveletFractalVector QuantizationData Compression
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在影像處理方面,小波轉換能將影像分解成高頻和低頻的部份,且具有能量集中和多重解析度的特性,不僅符合影像的靜態特性也完全符合人類的視覺系統,基於這些特性,能有效地增強影像壓縮系統的性能。而碎形影像壓縮為一新起發展的影像壓縮技術,近年來引起許多的研究和討論,其編碼的性能即使在相當高的壓縮率,所得到的重建影像能有一定的品質,在解碼的部份能即時(real-time)解碼,但在重建影像的高頻部份即影像中的邊緣輪廓(edge)和組織成份(texture)有訊息不足的現象。為了改善碎形編碼的性能,因此本篇論文結合了分頻,碎形和量化的影像壓縮方法,可以有效地提高壓縮比和改善影像的品質。
Fractal image coding has recently attracted a great deal of attention. But the coding performance tends to be deteriorated at the high resolution image blocks which generally include edges and fine textures. Wavelet representation of a finite energy signal with the combination of wavelet functions with similar basis is to decompose the image into a set of subimages at different spatial orientations and different resolutions. This enables us to have a multiscale representation of the image, which not only coincide with the image inherent statistical property but also match to characteristics of the human visual system perfectly, so that the image coding performance is excellent. In order to improve the performance of fractal image coding, this paper proposes a new coding scheme which is combined with vector quantization of multiresolution subimages. Experimental results have shown that the new scheme improves the compression ratio values and gets better image qualities.
誌謝 i
中文摘要 ii
英文摘要 iii
目錄 .iv
圖目錄 vi
表目錄 viii
第一章 緒論 1
1.1 無失真壓縮 1
1.2 失真壓縮 2
1.3 文獻探討 3
1.4 研究動機 6
第二章 小波轉換 7
2.1 小波的應用 7
2.2 尺度函數 9
2.3 多重解析度的分析 11
2.4 小波函數 12
2.5 正規化 14
2.6 Haar 小波函數 16
第三章 碎形影像壓縮 20
3.1 原始碎形 20
3.2 影像複製機 23
3.3 基本觀念 26
3.4 疊代系統 28
3.5 分割疊代系統 29
3.6 碎形影像編解碼 31
第四章 向量量化 33
4.1 向量量化編解碼 33
4.2 碼簿設計 35
第五章 在多重解析度的影像結合碎形影像壓縮和向量量化 37
5.1 分頻原理 37
5.2 演算法 38
第六章 模擬實驗 40
6.1 演算法的比較 40
6.2 性能的量測 42
6.3 實驗結果 42
第七章 結論 49
[1] H.-O. Peitgen, H. Jurgens, and D. Saupe, “Chaos and Fractals: New Frontiers of Science”. Berlin, Germany: Springer-Verlag, 1992.
[2] B.Mandelbrot, “The Fractal Geometry of Nature”, San Francisco, CA: Freeman, 1982.
[3] M.F. Barnsley and A.D. Sloan, “A better way to compress images”, Byte, vol.13, pp.215-223. Jan 1988.
[4] A. E. Jacquin, A Fractal Theory of Iterated Markov Operators with Applicatons to Digital Image Coding. Ph.D. thesis, Georgia Institute of Technology, August 1989.
[5] A. E. Jacquin, “Image coding based on a fractal theory of iterated contractive transformations,” IEEE Trans. on Image Processing, vol.1, no.1, pp.18-30. Jan.1992.
[6] Y. Fisher, E. W. Jacobs, and R. D. Boss, “Iterated transformation image compression”, NOSC Tech. Rep. Tr-1408, Naval Oceans Systems Center, San Diego, CA, 1991.
[7] E. W. Forgy, “Cluster Analysis of Multivariate Data: Efficiency vs. Interpretability of Classifications”. Abstract, Biometrics, vol. 21, pp. 768-769.
[8] Y. Linde, A. Buzo, and R. M. Gray, “An Algorithm for Vector Quantizer Design”, IEEE Trans. Commun., vol. COM-28, Jan. 1980, pp84-95.
[9] E.E. Hilbert, “Cluster Compression Algorithm- A Joint Clustering Data Compression Concept”. Technical Report. JPL Publication 77-43. Washington, DC: NASA, 1977.
[10] P.H. Westerink, D. E. Boekee, J. Biemond and J. W. Woods, “Subband Coding of Images using Vector Quantization”, IEEE Trans. Commun. vol. 36, no. 6, June 1988, pp.713-719.
[11] C.Sidney Burrus, Ramesh A. Gopinath, and Haitao Guo, Intoduction to Wavelets and Wavelet Transforms. Upper Saddle River, New Jersey: Prentice Hall,1998.
[12] Albert Boggess, Francis J. Narcowich, A First Course in Wavelets with Fourier Analysis. Upper Saddle River, New Jersey: Prentice Hall, 2001.
[13] M. Barnsley, “Fractals Everywhere” San Diego, Academic Press, 1988.
[14] A. E. Jacquin, “Fractal image coding: A review,” in Proc. IEEE, Oct. 1993, vol. 81, no. 10, pp. 1451-1465.
[15] E. W. Jacobs, Y. Fisher, and R. D. Boss, “Image compression: A study of the iterated transform method, “Signal Processing, vol.29, PP.251-263, 1992.
[16] Yuval Fisher, Fractal Image Compression Theory and Application. New York: Springer-Verlag, 1995.
[17] Zhengbing Zhang, “Fractal image compression based on wavelet transform” SPIE vol.3078, 0277-786x/97, PP198-205.
[18] Roberto Rinaldo and Giancarlo Calvagno, “Image Coding by Block Prediction of Multiresolution Subimages” IEEE Trans. Image Processing. 1995, PP909-920.
[19] R. M. Gray, “Vector quantization”, IEEE ASSP Magazine, Apr. 1984, PP4-29.
[20] W.H. Equitz, “A new vector quantization clustering algorithm”, IEEE Transactions on Acoustics, Speech, and Signal Processing, 37:1568-1575, October 1989.
[21] N. M. Nasrabadi, and R.A. King, “Image coding using vector quantization: A review”, IEEE Trans Commun., vol. 36, no.8, Aug. 1988,pp957-971.
[22] Khalid Sayood, Introduction to Data Compression. United Kingdom: Academic Press, Second Edition 2000.
[23] I. K. Kim and R.-H. Park, “Still image coding based on vector quantization and fractal approximation,” IEEE Trans. on Image Processing, vol.5, No.4, pp.587-597, Apr.1996.
[24] Brendt Wohlberg and Gerhard de Jager, “ A review of the fractal image coding literature”, IEEE Trans. on Image Processing, vol.8, No.12, pp.1716-1729, Dec.1999.
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