Combined Techniques Of Singular Value Decomposition and Vector Quantization For Image Coding

Jar Ferr Yang, Chiou Liang Lu

Research output: Contribution to journalArticlepeer-review

75 Citations (Scopus)

Abstract

The combination of singular value decomposition (SVD) and vector quantization (VQ) is proposed as a compression technique to achieve low bit rate and high quality image coding. Given a codebook consisting of singular vectors, two algorithms, which find the best-fit candidates without involving the complicated SVD computation, are described. Simulation results show that the proposed methods are better than the discrete cosine transform (DCT) in terms of energy compaction, data rate, image quality, and decoding complexity.

Original languageEnglish
Pages (from-to)1141-1146
Number of pages6
JournalIEEE Transactions on Image Processing
Volume4
Issue number8
DOIs
Publication statusPublished - 1995 Aug

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Graphics and Computer-Aided Design

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