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Image coding using adaptive vector quantization of wavelet coefficients
Author(s)
Date Issued
January 1, 2001
Type
Article
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 16 code vectors for 16 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 then be 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 36.3016, MSE = 15.2377, 1.03125 bpps.
Citation
Proceedings of SPIE the International Society for Optical Engineering, 4391, 191-196, 2001