研究生: |
張進邦 Chang, Jin-Bang |
---|---|
論文名稱: |
以DSP實現提升式離散小波轉換的影像壓縮之研究 DSP implementation of Lifting Scheme Wavelet Transform in Image Compression |
指導教授: |
廖德祿
Liao, Teh-Lu |
學位類別: |
碩士 Master |
系所名稱: |
工學院 - 工程科學系 Department of Engineering Science |
論文出版年: | 2006 |
畢業學年度: | 94 |
語文別: | 中文 |
論文頁數: | 56 |
中文關鍵詞: | 小波 、多重解析度理論 、影像金字塔 、數位信號處理器 、零樹壓縮 |
外文關鍵詞: | DSP, EZW, image pyramid, Multiresolution, Wavelet |
相關次數: | 點閱:89 下載:2 |
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摘要
在本論文中,將介紹離散小波轉換的影像壓縮編碼技術及其相關理論背景。提升式離散小波轉換(Lifting-based DWT)是以類似於預測編碼(predict encode)的小波架構,所轉換出來的小波係數與傳統濾波器方式相同,但相對所使用的硬體資源將大大減少,藉以改善傳統離散小波轉換的缺點。夲論文利用具有高運算效能的數位信號處理器(Didital Signal Processor, DSP)來實現所採用的提升式離散小波轉換應用於影像轉換與壓縮。所使用硬體發展平台為美商德州儀器所開發的TMS320C6713 DSK發展板,該發展板的核心為一顆具浮點運算的數位信號處理器TMS320C6713 DSP晶片。整篇論文的主要重點為利用提升式離散小波轉換小波轉換與逆轉換法應用於影像壓縮編碼作實現。
Abstract
In this thesis, we will discuss the theoretical backgrounds of discrete wavelet transform (DWT) in image processing. The Lifting-based Discrete Wavelet Transform (LDWT) has been proposed to reduce the complexity of hardware implementation. An image processing board based on TMS320C6713 DSK (TI, American), which can provide floating-point arithmetic and 8 parallel process capabilities, is designed to implement the Lifting-based Discrete Wavelet Transform and Lifting-based Inverse Discrete Wavelet Transform and apply to image compression and encoding.
參考文獻
[1] S. Mallat, “Multifrequency Channel Decompositions of Images and
Wavelet Models”, IEEE Trans. Acoust., Speech, Signal Process, vol. 37,pp. 2091-2110, 1989.
[2] M. N. Do, “Directional Multiresolution Image Representations , Ph.D.
Thesis,Department of Communication Systems, Swiss Federal Institute of Technology Lausanne, November 2001.
[3] ISO/IEC ISO/IEC 15444-1 "Information Technology JPEG 2000
Image Coding System", 2000.
[4] K. Parhi and T. Nishitani, “VLSI architectures for discrete
wavelet Transforms", IEEE Trans. VLSI Systems, vol. 1, no. 2, pp. 191-202, 1993.
[5] A. S. Lewis and G. Knowles, “VLSI architecture for 2-D
Daubechies wavelet transform without multipliers”, Electronic
Letters, vol.27, no.2 pp 171-173, 1991.
[6] W. Sweldens, “The Lifting Scheme: A Custom-Design Construction
of Biorthogonal Wavelet”, Applied and Computational Harmonic
Analysis, vol. 3, pp. 186-200, 1996.
[7] M. J. Shapiro. “Embedded Image Coding Using Zerotrees of
Wavelet Coefficients”. IEEE Transactions on Signal Processing,
Vol. 41, No. 12, pp. 3445-3462, December 1993.
[8] A. Said, and W. A. Pearlman. “A New, Fast, and Efficient
Image Codec Based on Set Partitioning in Hierarchical Trees”.
IEEE Transactions on Circuits and Systems for Video Technology, Vol. 6, No. 3, pp. 243-250, June 1996.
[9] D. Taubman. “High Performance Scalable Image Compression with
EBCOT”, IEEE Transactions on Image Processing, Vol. 9, No. 7, pp. 1158-1170, July 2000.
[10] M. Smith and T. Barnwell, “A Procedure for Designing Exact
Reconstruction Filter Banks for Tree-Structured Subband Coders”,
Proc. ICASSP, March 1984.
[11] Daubechies, “Time-Frequency Localization Operators: a Geometric
Phase Space Approach”. Information Theory, IEEE Transactions on, Volume 34, Issue 4, July 1988 Page(s):605 – 612.
[12] 陳同孝、黃國峰、張真誠,”數位影像處理技術”. September 2004.
[13] T.I. TMS320C6713 DSK Technical Reference, January 2004.
[14] T.I. TMS320C6713,TMS320C6713B FLOATING-POINT DIGITAL SIGNAL
PROCESSORS, March 2004,SPRS186H.
[15] T.I. TMS320C6x C Source Debugger User's Guide, January 1998,
SPRU188D.
[16] D.L. Wu, “Implementation of MP3 and Ogg Vorbis codec based on TMS320C6713 DSK”, Master Thesis of National Cheng Kung
University, June 2005.