TY - JOUR
T1 - Adaptive vector quantization with fuzzy distortion measure for image coding
AU - Pemmaraju, Suryalakshmi
AU - Mitra, Sunanda
AU - Long, L. Rodney
AU - Thoma, George R.
AU - Shieh, Yao Yang
AU - Roberson, Glenn H.
PY - 1996
Y1 - 1996
N2 - Despite the proven superiority of vector quantization (VQ) over scalar quantization (SQ) in terms of rate distortion theory, currently existing vector quantization algorithms, still, suffer from several practical drawbacks, such as codebook initialization, long search-process, and optimization of the distortion measure. We present a new adaptive vector quantization algorithm that uses a fuzzy distortion measure to find a globally optimum codebook. The generation of codebooks is facilitated by a self-organizing neural network-based clustering that eliminates adhoc assignment of the codebook size as required by standard statistical clustering. In addition, a multiresolution wavelet decomposition of the original image enhances the process of codebook generation. Preliminary results using standard monochrome images demonstrate excellent convergence of the algorithm, significant bit rate reduction, and yield reconstructed images with high visual quality and good PSNR and MSE. Extension of this adaptive VQ to color image compression is currently under investigation.
AB - Despite the proven superiority of vector quantization (VQ) over scalar quantization (SQ) in terms of rate distortion theory, currently existing vector quantization algorithms, still, suffer from several practical drawbacks, such as codebook initialization, long search-process, and optimization of the distortion measure. We present a new adaptive vector quantization algorithm that uses a fuzzy distortion measure to find a globally optimum codebook. The generation of codebooks is facilitated by a self-organizing neural network-based clustering that eliminates adhoc assignment of the codebook size as required by standard statistical clustering. In addition, a multiresolution wavelet decomposition of the original image enhances the process of codebook generation. Preliminary results using standard monochrome images demonstrate excellent convergence of the algorithm, significant bit rate reduction, and yield reconstructed images with high visual quality and good PSNR and MSE. Extension of this adaptive VQ to color image compression is currently under investigation.
UR - http://www.scopus.com/inward/record.url?scp=0029713975&partnerID=8YFLogxK
U2 - 10.1117/12.238494
DO - 10.1117/12.238494
M3 - Conference article
AN - SCOPUS:0029713975
VL - 2707
SP - 629
EP - 635
JO - Proceedings of SPIE - The International Society for Optical Engineering
JF - Proceedings of SPIE - The International Society for Optical Engineering
SN - 0277-786X
Y2 - 11 February 1996 through 11 February 1996
ER -