Adaptive image coding with perceptual distortion control

Ingo Höntsch, Lina Karam

Research output: Contribution to journalArticle

133 Scopus citations

Abstract

This paper presents a discrete cosine transform (DCT)-based locally adaptive perceptual image coder, which discriminates between image components based on their perceptual relevance for achieving increased performance in terms of quality and bit rate. The new coder uses a locally adaptive perceptual quantization scheme based on a tractable perceptual distortion metric. Our strategy is to exploit human visual masking properties by deriving visual masking thresholds in a locally adaptive fashion. The derived masking thresholds are used in controlling the quantization stage by adapting the quantizer reconstruction levels in order to meet the desired target perceptual distortion. The proposed coding scheme is flexible in that it can be easily extended to work with any subband-based decomposition in addition to block-based transform methods. Compared to existing perceptual coding methods, the proposed perceptual coding method exhibits superior performance in terms of bit rate and distortion control. Coding results are presented to illustrate the performance of the presented coding scheme.

Original languageEnglish (US)
Pages (from-to)213-222
Number of pages10
JournalIEEE Transactions on Image Processing
Volume11
Issue number3
DOIs
StatePublished - Mar 1 2002

Keywords

  • Image compression
  • Locally adaptive quantization
  • Perceptual distortion

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design

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