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

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2 Author(s)
Jincheng Huang ; Dept. of Electr. Eng., Polytech. Univ., Brooklyn, NY ; Yao Wang

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 128×128 24-b color ID image (49152 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

Published in:

IEEE Transactions on Image Processing  (Volume:8 ,  Issue: 1 )