Lapped nonlinear interpolative vector quantization and image super-resolution

David G. Sheppard, Kannan Panchapakesan, Ali Bilgin, Bobby R. Hunt, Michael W. Marcellin

Research output: Contribution to journalConference article

Abstract

This paper presents an improved version of an algorithm designed to perform image restoration via non-linear interpolative vector quantization (NLIVQ). The improvement results from using lapped blocks during the encoding process. The algorithm is trained on original and diffraction-limited image pairs. The discrete cosine transform is used in the codebook design process to control complexity. Simulation results are presented which demonstrate improvements over the non-lapped algorithm in both observed image quality and peak signal-to-noise ratio. In addition, the non-linearity of the algorithm is shown to produce super-resolution in the restored images.

Original languageEnglish (US)
Pages (from-to)224-228
Number of pages5
JournalConference Record of the Asilomar Conference on Signals, Systems and Computers
Volume1
StatePublished - Jan 1 1998
EventProceedings of the 1997 31st Asilomar Conference on Signals, Systems & Computers. Part 1 (of 2) - Pacific Grove, CA, USA
Duration: Nov 2 1997Nov 5 1997

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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