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Design of an Efficient Lossless CODEC for Wavelet Coefficients  

Lee, Seonyoung (School of Electronics and Information Engineering, Hankuk University of Foreign Studies)
Kyeongsoon Cho (School of Electronics and Information Engineering, Hankuk University of Foreign Studies)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SD / v.40, no.5, 2003 , pp. 335-344 More about this Journal
Abstract
The image compression based on discrete wavelet transform has been widely accepted in industry since it shows no block artifacts and provides a better image quality when compressed to low bits per pixel, compared to the traditional JPEG. The coefficients generated by discrete wavelet transform are quantized to reduce the number of code bits to represent them. After quantization, lossless coding processes are usually applied to make further reduction. This paper presents a new and efficient lossless coding algorithm for quantified wavelet coefficients based on the statistical properties of the coefficients. Combined with discrete wavelet transform and quantization processes, our algorithm has been implemented as an image compression chip, using 0.5${\mu}{\textrm}{m}$ standard cells. The experimental results show the efficiency and performance of the resulting chip.
Keywords
Image Compression; Discrete wavelet transform; Lossless coding;
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1 Mehran Aminian and Farzan Aminian, 'Neural-network based analog-circuit fault diagnosis using wavelet transform as preprocessor,' IEEE Trans. on Circuit and Systems-II: Analog and Digital Processing, vol. 47, no. 2, pp. 151-156, Feb. 2000   DOI   ScienceOn
2 Guoliang Fan and Xiang-Gen Xia, 'Improved hidden markov models in wavelet domain,' IEEE Trans. on Signal Processing, vol. 49, no. 1, pp. 115-120, Jan. 2001   DOI   ScienceOn
3 David S.Taubman and Michael W. Marcellin, JPEG 2000 : Image Compression Fundamentals, Standards and Practice, KAP, 2002
4 Aleksandra Mojsilovic, Miodrag V. Popovic and Dejan M. Rackov, 'On the selection of an optimal wavelet basis for texture characterization,' IEEE Trans. on Image Processing, vol. 9, no. 12, pp. 2043-2050, Dec. 2000   DOI   ScienceOn
5 D. A. Huffman, 'A method for the construction of minimum-redundancy codes,' Proc. of IRE, vol. 40, pp. 1098-1101, 1952   DOI   ScienceOn
6 S. Lee, K. Cho, and S. Hong, 'Design of a two-dimensional discrete wavelet transform core for image compression,' Journal of Korean Physics Society, vol. 38, no. 3, pp. 224-231, Mar. 2001
7 D. E. Thomas and P. R. Moorby, The Verilog Hardware Description Language, KAP, 1996
8 Samsung Electronics Co., Ltd., $0.5{\mu}m$ High Density CMOS Standard Cell Library Data Book, June 1997
9 I. Daubechies, 'Orthonormal bases of compactly supported wavelets,' Communication Pure Applied Math., vol. 41, pp. 909-996, Nov. 1988   DOI
10 Samsung Electronics Co., Ltd., KM416S1120D : IM ${\times}$ 16 SDRAM, Revision 1.4, June 1999
11 S. G. Mallat, 'A theory for multiresolution signal decomposition : The wavelet representation,' IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 11, no. 7, pp. 674-693, July 1989   DOI   ScienceOn
12 A. Grzeszczak, M. K. Mandal, S. Panchanathan and T. Yeap, 'VLSI implementation of discrete wavelet transform,' IEEE Trans. on VLSI Systems, vol. 4, no. 4, pp. 421-433, Dec. 1996   DOI   ScienceOn
13 Nick Soveiko and Michel S. Nakhla, 'Efficient capacitance extraction computations in wavelet domain,' IEEE Trans. on Circuit and System-I: Fundamental Theory and Applications, vol. 47, no. 5, pp. 684-701, May 2000   DOI   ScienceOn
14 M. Vishwanath, R. M. Owens and M. J. Irwin, 'VLSI architectures for the discrete wavelet transform,' IEEE Trans. on Circuits and Systems-II: Analog and Digital Signal Processing, vol. 42, no. 5, pp. 305-316, May 1995   DOI   ScienceOn