Indicator elimination for locally adaptive scheme using data hiding technique

Hon Hang Chang, Yung Chen Chou, Timothy K. Shih

Research output: Contribution to journalArticlepeer-review

Abstract

Image compression is a popular research issue that focuses on the problems of reducing the size of multimedia files. Vector Quantization (VQ) is a well-known lossy compression method which can significantly reduce the size of a digital image while maintaining acceptable visual quality. A locally adaptive scheme (LAS) was proposed to improve the compression rate of VQ in 1997. However, a LAS needs extra indicators to indicate the sources, consequently the compression rate of LAS will be affected. In this paper, we propose a novel method to eliminate the LAS indicators and so improve the compression rate. The proposed method uses the concept of data hiding to conceal the indicators, thus further improving the compression rate of LAS. From experimental results, it is clearly demonstrated that the proposed method can actually eliminate the extra indicators while successfully improving the compression rate of the LAS.

Original languageEnglish
Pages (from-to)4624-4642
Number of pages19
JournalKSII Transactions on Internet and Information Systems
Volume8
Issue number12
DOIs
StatePublished - 31 Dec 2014

Keywords

  • Data hiding technique
  • Image compression
  • Locally adaptive scheme
  • Vector quantization

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