博碩士論文 89521001 詳細資訊




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姓名 林桂蘭(Kuei-Lan Lin)  查詢紙本館藏   畢業系所 電機工程學系
論文名稱 JPEG2000靜態影像編碼系統之分析與架構設計
(Analysis and Architecture Design for JPEG2000 Still Image Encoding System)
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摘要(中) 近年來隨著數位影像應用的普及,一個能夠提供具有效率的表示方式及支援更多功能的靜態影像壓縮標準於焉而生。新一代的靜態影像壓縮標準JPEG2000與目前現存的影像壓縮標準比較起來,不只擁有更高的壓縮效率,還提供了多種功能,並可廣泛的應用在各種領域中。
本論文將針對JPEG2000靜態影像編碼系統作一分析與及其架構的設計。我們首先介紹JPEG2000編碼系統的編碼流程及基本原理,此系統主要包括三個主要功能方塊:離散小波轉換 (DWT)、純量量化以及採用EBCOT演算法的熵編碼。接著分析整個系統的複雜度,我們可經由實驗結果發現JPEG2000編碼系統的瓶頸在於EBCOT方塊編碼器。因此在本論文中,我們討論了幾種可以降低EBCOT編碼器運算時間的策略。在演算法的改良上,我們設計了兩種加速方法:CUPS (Clean Up Pass Skipping) 和PP (Pass Predicting) ,並經實驗證明了運用這兩種加速方法可以有效的降低EBCOT context產生器平均43%的運算時間。
另外,我們也完成了一個有效率的JPEG2000編碼系統硬體架構設計。在小波轉換的部分,提出了一個運用最簡運算單元來實現新一代小波(亦即lifting scheme)演算法的摺疊式架構,此架構具有較高的硬體使用率及較低的面積花費。對於純量量化器的設計,配合後續的EBCOT context產生器,我們採用與JPEG2000標準相容且最簡單的方式去實現。在EBCOT演算法方面,我們將前面所提出的加速演算法CUPS與PP加入,提出了一個硬體架構設計。本論文中所提出的加速演算法CUPS,僅需要一累加器去加總已編碼過的位元數目即可達成。加速演算法PP則需要額外的組合邏輯電路及兩塊記憶體來紀錄預測下一位元平面編碼掃描的情況。這些許的元件可使得整個EBCOT的編碼速度上更有效率。
摘要(英) Since the usage for digital imagery becoming popular in our world today, the still image compression standards that are able to provide the efficient representation and more features for different application are necessary. A new still image standard, JPEG2000, supplies not only higher compression performance but also various functionalities. Thus the commonly used standard, JPEG, can’t contend with.
This thesis focuses on the analysis and architecture design for a JPEG2000 still image encoding system. We firstly introduce the fundamental concepts of JPEG2000 encoding system. It consists of three major block, DWT, scalar quantization, and EBCOT. Then we analyze this system with several experiments. Based on the experiment results, the bottleneck for JPEG2000, EBCOT, is found. In this regard, some strategies for decreasing the computation time of EBCOT are discussed. In order to improve the EBCOT algorithm, Clean Up Pass Skipping method (CUPS) and Pass Predicting method (PP) are proposed. We verify the CUPS and PP methods by completed simulation on VC++ environment and they can reduce the 43% clock cycles for EBCOT context modeling.
Moreover, we achieve the efficient hardware architecture for the JPEG2000 encoding system. A new folded architecture for lifting-based DWT is presented. This design has the advantages of high hardware utilization and low area consumption. The architecture design for scalar quantization with VTQ is implemented. Using VTQ helps with reducing the computation time for EBCOT more efficiently than using DTQ. For the architecture design of EBCOT context modeling, proposed speed-improved methods are included. The CUPS method only needs an accumulator to sum up the number of coefficient-bits in a bitplane that have been coded in Pass1 and Pass2. The PP method requires extra combinational logic circuits and two predict tables to record the addresses when the Pass1 and Pass2 coding are needed. A few components can improve the speed efficiency.
關鍵字(中) ★ 影像壓縮
★ 方塊編碼
★ 小波轉換
★ 架構設計
關鍵字(英) ★ architecture design
★ DWT
★ JPEG2000
★ EBCOT
論文目次 CHAPTER 1 INTRODUCTION 1
1.1 BACKGROUND 1
1.2 JPEG2000 OVERVIEW 2
1.2.1 Features and Application for JPEG2000 2
1.2.2 JPEG2000 Encoding Process 3
1.3 THESIS ORGANIZATION 4
CHAPTER 2 FUNDAMENTAL CONCEPTS OF JPEG2000 ENCODING SYSTEM 5
2.1 DISCRETE WAVELET TRANSFORM (DWT) 5
2.1.1 Classical Wavelet Transform 6
2.1.2 Lifting-Based Wavelet Transform 9
2.1.3 Complexity Comparison of Convolution vs. Lifting-based Discrete Wavelet Transform 12
2.2 UNIFORM SCALAR QUANTIZATION 13
2.3 EMBEDDED BLOCK CODING WITH OPTIMIZED TRUNCATION (EBCOT) 15
CHAPTER 3 ANALYSIS AND SPEED-IMPROVED METHODS OF JPEG2000 ENCODING SYSTEM 23
3.1 ANALYSIS OF JPEG2000 ENCODING SYSTEM 23
3.2 ANALYSIS OF QUANTIZATION EFFECT 24
3.3 ANALYSIS OF EBCOT 28
3.3.1 Preliminary 29
3.4 SPEED-IMPROVED METHOD 31
3.4.1 Clean Up Pass Skipping Method (CUPS Method) 31
3.4.2 Pass Predicting Method (PP Method) 33
3.5 QUANTIZATION EFFECT TO CUPS AND PP METHODS 39
CHAPTER 4 ARCHITECTURE DESIGN OF JPEG2000 ENCODING SYSTEM 41
4.1 ARCHITECTURE DESIGN OF LIFTING-BASED DWT 41
4.1.1 1-D DWT 41
4.1.2 Design and Simulation Result 46
4.1.3 2-D DWT 48
4.2 ARCHITECTURE DESIGN FOR UNIFORM SCALAR QUANTIZATION 49
4.3 ARCHITECTURE DESIGN FOR EBCOT CONTEXT MODELING 50
4.4 SYSTEM INTEGRATION 55
CHAPTER 5 CONCLUSIONS AND FUTURE WORK 58
REFERENCE 60
參考文獻 [1] W. B. Pennebaker and J. L. Mitchell, JPEG Still Image Data Compression Standard, Van Nostrand Reinhold, New York 1993.
[2] V. Bhaskaran, and K. Konstantinides, Image and Video Compression Standard: Algorithms and Architecture, Kluwer Academic Publishers, 2nd edition, 2000.
[3] JPEG-2000 Part1 Final Committee Draft Version 1.0, ISO/IEC JTC1/SC29/WG1 N1646R, 2000.
[4] JPEG-2000 Verification Model 7.0, ISO/IEC JTC1/SC29/WG1 N 1684, 2000.
[5] JPEG2000 Verification Model Software Version 7.2, ISO/IEC JTC1/SC29/WG1 N1699.
[6] D. Taubman, M. Marcellin, JPEG2000 Image Compression Fundamentals, Standards and Practice, Kluwer Academic Publishers, 2002.
[7] A. N. Skodras, C. A. Christopoulos and T. Ebrahimi, “JPEG2000: The upcoming still image compression standard,” Proc. of the 11th Portuguese Conference on Pattern Recognition, pp. 359-366, 2000.
[8] M. Gormish, D. Lee, M. Marcellin, “JPEG2000: Overview, Architecture, and Applications,” Proc. of IEEE International Conference on Image Processing (ICIP), Vancouver, Canada, 2000.
[9] A. Perkis, Daniel G. Cardelo, “Transmission of Still Images over Noisy Channels,” ISSPA ’99, Australia pp. 789-793, 1999.
[10] H. Man, F. Kossentini, M. J. T. Smith, “An error resilient coding technique for JPEG2000,” Proc. of IEEE International Conference on Image Processing, vol. 3, pp. 364-367, 2000.
[11] C. Christopoulos, J. Askelof, M. Larsson, “Efficient Region of Interest Coding Techniques in the Upcoming JPEG2000 Still Image Coding Standard,” Proc. of IEEE International Conference on Image Processing (ICIP), Vancouver, Canada, 2000.
[12] S. Mallat, “A theory for multiresolution signal decomposition: The wavelet representation,” IEEE Trans. Pattern Anal. And Machine Intell., vol. 11, no. 7, pp. 674-693, July 1989.
[13] G. Strang and T. Nguyen. Wavelets and Filter Banks. Wellesley, Cambridge, 1996.
[14] M. Vetterli and J. Kovaĉević. Wavelets and Subband Coding. Prentice Hall, Englewood Cliffs, NJ, 1995.
[15] I. Daubechies and W. Sweldens, “Factoring Wavelet Transforms into Lifting Steps,” Industrial Mathematics Initiative, Department of Mathematics, University of South Carolina, 1995.
[16] W. Sweldens, “The lifting scheme: A new philosophy in biorthogonal wavelet constructions,” Proc. SPIE Wavelet Application in Signal and Image Processing III, pp. 68-79, 1995.
[17] M. W. Marcellin, M. A. Lepley, A. Bilgin, T. J. Flohr, T. T. Chinen, J. H. Kasner, “An Overview of Quantization in JPEG-2000,” (invited paper) Signal Processing: Image Communications, Special Issue on JPEG-2000, vol.17/1, pp. 73-84, December 2001.
[18] J. M. Shapiro, “An Embedded Hierarchical Image Coder Using Zerotrees of Wavelet Coefficients,” Proc. Of IEEE Data Compression Conference, (Snowbird, Utah), pp.214-223, 1993.
[19] A. Said and W. Pearlman, “A New, Fast and Efficient Image Codec Based on Set Partitioning in Hierarchical Trees,” IEEE Trans. Circuits and Systems for Video Technology, pp. 243-250, 1996.
[20] D. Taubman, “High performance scalable image compression with EBCOT,” Proc. Of IEEE International Conference on Image Processing (ICIP), Kobe, Japan, vol. 3, pp. 344-348, 1999.
[21] D. Taubman, “High performance scalable image compression with EBCOT,” IEEE Transactions on Image Processing, vol. 9, pp. 1158-1170, 2000.
[22] D. Taubman, E. Ordentlich, M. Weinberger, G. Seroussi, I. Ueno, F. Ono, “Embedded Block Coding in JPEG2000,” Proc. of IEEE International Conference on Image Processing, vol. 2, pp. 33-36, 2000.
[23] H. Witten, R. M. Neal, and J. G. Cleary, “Arithmetic coding for data compression,” Communication of the ACM, vol. 30, no. 6, pp. 520-540, 1987.
[24] M. J. Slattery and J. L. Mitchell, “The Qx-coder,” IBM Journal of Reserch and Development, vol.42, No. 6, 1998.
[25] J. Li and S. Lei, “An embedded still image coder with rate-distortion optimization,” IEEE Trans. Image Processing, vol. 8, no. 7, pp. 913-924, 1999.
[26] C. C. Liu, Y. H. Shiau, J. M. Jou, “Design and Implementation of a Progressive Image Coding Chip Based on the Lifted Wavelet Transform,” The 11th VLSI Design/CAD Symposium, August 2000.
[27] C. J. Lian, K. F. Chen, H. H. Chen, L. G. Chen, “Lifting Based Discrete Wavelet Transform Architecture for JPEG2000”.
[28] K. F. Chen, C. J. Lian, H. H. Chen, L. G. Chen, “Analysis and architecture design of EBCOT for JPEG-2000,” The 2001 IEEE International Symposium on Circuits and Systems, vol. 2, pp. 765-768, 2001.
[29] K. K. Parhi, VLSI Digital Signal Processing Systems: Design and Implementation, A Wiley-Interscience Publication, 1999.
[30] Y. H. Shiau, Y. T. Hu, S. r. Kuang, and J. M. Jou, “System design of JPEG2000 still image compression coder,” Proc. of the 12th VLSI Design/CAD Symposium, Taiwan, 2001.
指導教授 蔡宗漢(Tsung-Han Tsai) 審核日期 2002-7-15
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