Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/7430
標題: SPIHT影像編解碼於多媒體應用之有效成本設計與實現
Cost effective design and implementation of SPIHT image codec for multimedia applications
作者: 許智凱
Hsu, Chih-Kai
關鍵字: Wavelet;小波轉換;SPIHT;block based on coding;集合分割階層樹狀結構編碼法;區塊化編碼
出版社: 電機工程學系所
引用: [1] 戴顯權,陳政一,“JPEG2000,”紳籃出版社,2002 [2] 吳炳飛、胡益強、瞿忠正、蘇崇彥、林重甫,“JPEG 2000影像壓縮技 術,”全華出版社,2003. [3] 溫國瑋,“區塊重排於小波封包之階層式集合分割影像壓縮技術,”國立中央大學電機工程研究所,碩士論文,2002. [4] JPEG 2000 Part I Final Committee Draft Version 1.0, ISO/IEC/JTC1/SC29/WG1N1646R, March 2000. [5] M. J. Gormish, D. Lee and M. W. Marcellin, “JPEG2000:Overiew, Architecture, and Applications,” Ricoh California research center. [6] N. Skodras, C. A. Christopoulos and T. Ebrahimi, “JPEG2000: The upcoming still image compression standard,” Proceeding of the 11th Portuguese Conference on Pattern Recognition, pp.359~366, May 2000 [7] J. M. Sharpiro, “An Embedded Hierarchical Image Coder Using Zerotrees of Wavelet Coefficients,” Proc, of IEEE Data Compression Conference (Snowbird, Utah). pp.214-223, 1993 [8] A. Said and W. A. Pearlman,"A new fast and efficient image codec based on set partitioning in hierarchical tree", IEEE Trans. Circuits and Systems foe Video Technology, Vol.6, No.3,jun 1996. [9] G. Strang and T. Nguyen, Wavelet and Filter Banks, lst ed. Wellesley, MA:Wellesley-Cambridge Press, 1996. [10] S. Mallat, A Wavelet Tour of Signal Processing, San Diego:Academic Press, 1998. [11] S. Mallat, “A Theory for Multiresolution Signal Decomposition:The Wavelet Representation,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 11:674-693, 1989. [12] R. Coifman, Y. Meyer, S. Quake, and V. Wickerhauser, “Singal Processing and Compression with Wavelet Packets,” Numerical Algorithms Research Group, Yale University, 1990. [13] I. Daubechies and W. Sweldens, “Factoring wavelet transforms into lifting scheme,” The J. of Fourier Analysis and Applications vol. 4, pp. 247-269, 1998. [14] W. Sweldens, “The lifting scheme: A custom-design construction of biorthogonal wavelets,” Applied and Computation Harmonic Analysis, vol. 3, pp.186-200. [15] W. Sweldens, “The lifting scheme: A construction of second-generation wavelets,” Siam Journal of Mathematical Analysis, vol. 29,pp.511-200, 1997. [16] F. W. Wheeler, W. A. Pearlman “SPIHT Image Compression Without Lists”,ICASSP 2000,CDROM IV2047-2050 [17] C. T. Huang, P. C. Tseng, and L. G.. Chen, “Flipping structure: An efficient VLSI architecture for lifting-based discrete wavelet transform.” IEEE Trans. Signal Process., vol. 52. no. 4, pp. 1080-1089, Apr. 2004. [18] P. C. Tseng, C. T. Huang, and L. G. Chen, “Generic RAM-based architecture for two-dimensional discrete wavelet transform with line-based method” [19] H. Liao, M. K. Mandal, and B. F. Cockburn, “Efficient architectures for 1-D and 2-D lifting-based wavelet transforms,” IEEE Trans. Signal Process., vol.52, no.5,pp. 1315-1326, May 2004. [20] M. Antonini, M. Barlaud, P. Mathieu, and I. Daubechies, “Image coding using wavelet transform,” IEEE Trans. Image Processing, vol. 1, pp. 205-220, Apr.1992. [21] Shen-Fu Hsiao, Yor-Chin Tai and Kai-Hsiang Chang, “VLSI DESIGN OF AN EFFICIENT EMBEDDED ZEROTREE WAVELET CODER WITH FUNCTION OF DIGITAL WATERMARKING,” IEEE Transactions on Consumer Electronics, Vol. 46, No. 3, AUGUST 2000 [22]Li-minn Ang, Hon Nin Cheung and Kamran Eshraghian, “A DATAFLOW-ORIENTED VLSI ARCHITECTURE FOR A MODIFIED SPIHT ALGORITHM USING DEPTH-FIRST SEARCH BIT STREAM PROCESSING,” ISCAS 2000 - IEEE International Symposium on Circuits and Systems, May 28-31, 2000 [23] Win-Bin Huang, Yuan-Jui Chang, Alvin W.Y. Su and Yau-Hwang Kuo,“VLSI Design Of A DWT/Modified Efficient SPIHT Based Image Codec,” ICICS-PCM 2003 [24] Yin-Tsung Hwang, Kuei-Hung Cheng, Li-Chun Liang and Cheng-Chen Lin, “A NOVEL WAVELET COEFF''ICIENTS CODING SCHEME AND ITS FPGAREALIZATION,” The 2004 IEEE Asia-Pacific Conference on Circuits and Systems, December 6-9,2004 [25] Karl Martin, Rastislav Lukac, Konstantinos N. Plataniotis, “Efficient Encryption of Compressed Color Images,” IEEE ISIE 2005, June 20-23, 2005 [26] Li-miriiz Aizg, Hon Nin Cheung, “HARDWARE IMPLEMENTATION OF THEDEPTH FIRST SEARCH BIT STREAM SPIHT SYSTEM,” IEEE 2001, ,pp.518-521 [27] J. Singh. A. Antoniou, and D. J. Shpak, “Hardwxe Implementation of a: Wavelet based Image Compression Coder,” IEEE 1998, ,pp.169-173 [28]Maurizio Martina, Andrea Molino, Andrea Teweno, Fabrizio Vacca, “IMPLEMENTATION OF A SPIHT COPROCESSOR MEMORY ISSUES AND HARDWARE IMPLICATIONS,” IEEE 2003,II587-590 [29] Thomas W. Fry, Scott Hauck,“SPIHT Image Compression on FPGAs” [30]Wen-Kuo Lin and Neil Burgess, “Listless Zerotree Coding for Color Images,” IEEE1998,pp231-235 [31]Wen-Kuo Lin and Neil Burgess, “LOW MEMORY COLOR IMAGE ZEROTREE CODING,” IEEE1999,pp91-95
摘要: 
現今在網路上傳輸影音資訊相當頻繁,尤其影像資訊最佔頻寬。若在有限的頻寬下傳輸影像資訊,則更增加許多傳輸時間。及若在有限的儲存空間下儲存影像資訊,則影像張數也受限制。
因此影像壓縮就格外的重要,即可減少影像資訊傳輸的傳輸量及增加儲存影像張數。在靜態影像壓縮中,小波轉換提供了最好的影像編碼效果。
在小波轉換的基礎下,SPIHT〝Set Partitioning In Hierarchical Tree〞(集合分割階層樹狀結構編碼法)普遍運用在影像編碼壓縮上。其中主要功能就是要達到漸進式傳輸,及準確的控制編碼長度。
在SPIHT演算法硬體化中,需要使用許多暫存器來來記錄搜尋像素座標。所以所需的暫存器會隨著處理影像大小增加而增加,因此若將影像加以切割,即使用影像區塊化編碼即可解決這個問題。
在本論文中針對區塊化作了許多實驗與評估,評估區塊化對編碼效能之影響程度,及評估區塊化對影像品質之影響程度。
並且對SPIHT演算法加以硬體化,以及對編解碼加以整合。且運用小波轉換特性,及SPIHT編碼特性來提升漸進式編碼效果。

Nowadays, we frequently transmit the audio and image information in the network. We find out that the image information needs most of the bandwidth. If the image information is transmitted in a limited bandwidth, the transmission time would increase. If the image information is stored in a limited space, the number of image is also restricted.
Then we know the compressed image is very important. It can reduce that the amount of image information. The wavelet transform supports the best result of compressed image in the static image compressor.
Under the foundation of wavelet transform, SPIHT(Set Partitioning In Hierarchical Tree) is generally used in compressing the image. It has two main functions: one is to get up to progressive transmission. The other is to accurately control the length of coding.
While using VLSI to accomplish SPIHT algorithm, it needs to use a lot of registers to record the coordinates of pixel. As the size of image increase, the registers will increase. If we cut the image in pieces and use block based on coding, then we can solve this problem.
This paper makes a lot of experiments and assessments for block based on SPIHT coding. It assesses efficiency and image quality based on SPIHT coding…etc.
This paper accomplished SPIHT image codec in the FPGA. Furthermore, It uses characteristics of the wavelet transform and the SPIHT coding to improve the result of the progressive coding.
URI: http://hdl.handle.net/11455/7430
其他識別: U0005-0907200723160600
Appears in Collections:電機工程學系所

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