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Proceedings Paper

Image coding using adaptive vector quantization of wavelet coefficients
Author(s): Sakreya Chitwong; Fusak Cheevasuvit; J. Sinthuvanichsaid
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Paper Abstract

In this paper we propose a subband image compression by using wavelet transform to split original images. Each of subband images is then quantized by an adaptive vector quantization with dynamic bit allocation based on advantage of nature of wavelet coefficients. The energy of each subband image, except the lowest frequency subband image will not be quantized, will be sorted from minimum to maximum. Energy of each subband image is calculated to allocate bits not over the desired bit rate. The accumulation of energy from these subband images will be divided into 4 groups. First two lower energy groups will be encoded with 256 and 1 6 code vectors for 1 6 pixels block size in accordance with energy ratio. Others will be encoded with 256 code vectors for 4 and 16 pixels block size. Based on the given bit rate, the total dynamical bit rate of each group is calculated. If the total dynamical bit rate in the group is less or more than the given bit, it will thenbe adjusted based on the energy of subband image in only the same group. The remaining of energy from higher energy group will be carried to lower. The experiments are shown that the resulting images from the proposed method can be clearly improved by Peak Signal to Noise Ratio (PSNR) of 36.30 16, MSE =15.2377, 1 .03 125 bpps.

Paper Details

Date Published: 26 March 2001
PDF: 6 pages
Proc. SPIE 4391, Wavelet Applications VIII, (26 March 2001); doi: 10.1117/12.421199
Show Author Affiliations
Sakreya Chitwong, King Mongkut's Institute of Technology Ladkrabang (Thailand)
Fusak Cheevasuvit, King Mongkut's Institute of Technology Ladkrabang (Thailand)
J. Sinthuvanichsaid, Dhurakijpundit Univ. (Thailand)


Published in SPIE Proceedings Vol. 4391:
Wavelet Applications VIII
Harold H. Szu; David L. Donoho; Adolf W. Lohmann; William J. Campbell; James R. Buss, Editor(s)

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