Research and Progress of Image Compression Coding Based on Wavelet

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Abstract:

Image compression is a technology using as little as possible bits to represent the original image. As wavelet transform has local characteristics on the time and frequency domain, it makes up the deficiency of DCT. Moreover, its multi-resolution characteristics can easily associate with the human visual system (HVS). Besides, wavelet-based image compression is prone to combine with new image coding methods. It has become the research hotspots at present. This paper introduces wavelets theory and discusses the research status and progress of wavelet-based image compression then points out the main problems. Finally, the prospect in the future was presented.

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Advanced Materials Research (Volumes 403-408)

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1352-1355

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November 2011

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] Mallat·S·G, A theory for multi-resolution signal decomposition: the wavelet representation,. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1989, 11 (7): 674 - 693.

DOI: 10.1109/34.192463

Google Scholar

[2] Daubechies I, The wavelet transform: time- frequency localization and signal analysis,. IEEE Trans IT, 1990, 961-1006.

DOI: 10.1109/18.57199

Google Scholar

[3] Antonini M, Barland M, Mathieu P, et a1, Image Coding Using Wavelet Transform,. IEEE Trans· on Image Processing, 1992, 38 (2) : 244-250.

DOI: 10.1109/83.136597

Google Scholar

[4] Shapiro JM, Embedding image coding using zero trees of wavelet coefficients,. IEEE Trans: on Signal Processing, 1993, 41(12): 3445-3462.

DOI: 10.1109/78.258085

Google Scholar

[5] A Said, W A Pearlman, A new fast and efficient image codec based on set partitioning in hierarchical trees,. IEEE Trans. on Circuits and Systems for Video Tech. 1996, 6(3): 243-250.

DOI: 10.1109/76.499834

Google Scholar

[6] D Taubman, High performance scalable image compression with EBCOT,. IEEE Transactions on Image Processing, 2000, 9(7): 1158-1170.

DOI: 10.1109/83.847830

Google Scholar

[7] Geronimo J S, Hardin D P, Massopust P R, Fractal functions and wavelet expansions based on several scaling functions,. J of Approx Theory , 1994 , 78 : 373-401.

DOI: 10.1006/jath.1994.1085

Google Scholar

[8] XU Linjing, Meng Limin, Zhu Jianjun, The Comparision and Application Between Wavelet and Fractal in Image Compressing,. China CATV Journal, Z1 (2003) 26-29.

Google Scholar

[9] Taekon Kim, Robert E . Van Dyck, David J. Miller, Hybrid fractal zerotree wavelet image coding,. Signal Processing: Image Communication, 2002, 17: 347-360.

DOI: 10.1016/s0923-5965(02)00003-6

Google Scholar

[10] Chun-lin SONG, Rui FENG, et al, A Novel Fractal Wavelet Image Compression Approach,. Journal of China University of Mining and Technology, 2007, 17(1): 121-125.

DOI: 10.1016/s1006-1266(07)60026-1

Google Scholar

[11] J.N. Ellinas, M. S. Sangriotis, Morphological wavelet-based stereo image coders,. J. Vis. Commun. Image R. 2006, 17: 686-700.

DOI: 10.1016/j.jvcir.2005.10.005

Google Scholar