Title :
Compression of color facial images using feature correction two-stage vector quantization
Author :
Jincheng Huang ; Yao Wang
Author_Institution :
Dept. of Electr. Eng., Polytech. Univ., Brooklyn, NY
fDate :
1/1/1999 12:00:00 AM
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 128×128 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
Keywords :
Huffman codes; Karhunen-Loeve transforms; image coding; image colour analysis; transform coding; vector quantisation; 128 pixel; 16404 pixel; 24 bit; 450 byte; 49152 byte; 500 byte; FC2VQ algorithm; ID pictures; KLT color spaces; Karhunen-Loeve transform; RGB; RGB-FC2VQ; YCbCr; YCbCr-FC2VQ; codeword indices; color facial images; color images; feature correction two-stage vector quantization; first order Huffman coder; image quality; photo identification pictures; Color; Eyes; Facial features; Gray-scale; Huffman coding; Image coding; Image quality; Mouth; Transform coding; Vector quantization;
Journal_Title :
Image Processing, IEEE Transactions on
