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

Jincheng Huang, Yao Wang

Research output: Contribution to journalArticle

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 (49 152 bytes) can be compressed down to about 500 bytes with satisfactory quality. When the codeword indices are further compressed losslessy using a first order Huffman coder, this size is further reduced to about 450 bytes.

Original languageEnglish (US)
Pages (from-to)102-109
Number of pages8
JournalIEEE Transactions on Image Processing
Volume8
Issue number1
DOIs
StatePublished - 1999

Fingerprint

Vector Quantization
Vector quantization
Compression
Color
Transform
Color Space
Color Image
Image Quality
Image quality
First-order

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Graphics and Computer-Aided Design
  • Software
  • Theoretical Computer Science
  • Computational Theory and Mathematics
  • Computer Vision and Pattern Recognition

Cite this

Compression of color facial images using feature correction two-stage vector quantization. / Huang, Jincheng; Wang, Yao.

In: IEEE Transactions on Image Processing, Vol. 8, No. 1, 1999, p. 102-109.

Research output: Contribution to journalArticle

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