Adaptive image coding using spectral classification

Hamid Jafarkhani, Nariman Farvardin

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

We present a new classification scheme, dubbed spectral classification, which uses the spectral characteristics of the image blocks to classify them into one of a finite number of classes. A vector quantizer with an appropriate distortion measure is designed to perform the classification operation. The application of the proposed spectral classification scheme is then demonstrated in the context of adaptive image coding. It is shown that the spectral classifier outperforms gain-based classifiers while requiring a lower computational complexity.

Original languageEnglish
Pages (from-to)605-610
Number of pages6
JournalIEEE Transactions on Image Processing
Volume7
Issue number4
DOIs
StatePublished - 1998

Keywords

  • Classification
  • Discrete cosine transform
  • Image coding
  • Trellis-coded quantization
  • Wavelet transform

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