Vector quantizer for image restoration

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

Research output: Contribution to conferencePaper

2 Scopus citations

Abstract

An algorithm based on nonlinear interpolative vector quantization (NLIVQ) is presented which accomplishes image restoration concurrently with image compression. The algorithm is applied to the problem of deblurring noise-free diffraction-limited images by training with a large set of blurred and original image pairs. Simulation results demonstrate a quantitative improvement in images processed by the algorithm, as measured by image peak signal-to-noise ratio (PSNR), as well as a significant improvement in perceived image quality. A theoretical formulation of the algorithm is presented along with a discussion of implementation, training and simulation results.

Original languageEnglish (US)
Pages439-441
Number of pages3
StatePublished - Dec 1 1996
EventProceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3) - Lausanne, Switz
Duration: Sep 16 1996Sep 19 1996

Other

OtherProceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3)
CityLausanne, Switz
Period9/16/969/19/96

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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    Sheppard, D. G., Bilgin, A., Hunt, B. R., Marcellin, M. W., & Nadar, M. S. (1996). Vector quantizer for image restoration. 439-441. Paper presented at Proceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3), Lausanne, Switz, .