Compression of color facial images using feature correction two-stage vector quantization

Abstract

A feature correction two-stage vector quantization (FC2VQ) algorithm was previously developed to compress gray-scale photo identification (ID) pictures. This algorithm is extended to color images in this work. Three options are compared, which apply the FC2VQ algorithm in RGB, YCbCr, and Karhunen-Loeve transform (KLT) color spaces, respectively. The RGB-FC2VQ algorithm is found to yield better image quality than KLT-FC2VQ or YCbCr-FC2VQ at similar bit rates. With the RGB-FC2VQ algorithm, a 128 x 128 24-b color ID image (49,152 bytes) can be compressed down to about 500 bytes with satisfactory quality. When the codeword indices are further compressed losslessly using a first order Huffman coder, this size is further reduced to about 450 bytes.

DOI: 10.1109/83.736696

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Cite this paper

@article{Huang1999CompressionOC, title={Compression of color facial images using feature correction two-stage vector quantization}, author={Jincheng Huang and Yao Wang}, journal={IEEE transactions on image processing : a publication of the IEEE Signal Processing Society}, year={1999}, volume={8 1}, pages={102-9} }