A vector quantizer for image restoration

David G. Sheppard, Ali Bilgin, Mariappan S. Nadar, Bobby R. Hunt, Michael W. Marcellin

Research output: Contribution to journalArticlepeer-review

21 Scopus citations


This paper presents a novel technique for image restoration based on nonlinear interpolative vector quantization (NLIVQ). The algorithm performs nonlinear restoration of diffraction-limited images concurrently with quantization. It is trained on image pairs consisting of an original image and its diffraction-limited counterpart. The discrete cosine transform is used in the codebook design process to control complexity. Simulation results are presented that demonstrate improvements in visual quality and peak signal-to-noise ratio of the restored images.

Original languageEnglish (US)
Pages (from-to)119-124
Number of pages6
JournalIEEE Transactions on Image Processing
Issue number1
StatePublished - 1998


  • Image restoration
  • Nonlinear image processing
  • Nonlinear interpolation
  • Vector quantization

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design


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