Blur identification from vector quantizer encoder distortion

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In this work, a method is presented for image blur identification from vector quantizer (VQ) encoder distortion. The method requires a set of training images produced by each member of a set of candidate blur functions. Each of these sets is then used to train a VQ encoder. Given an image degraded by an unknown blur function, the blur function can be identified by choosing from among the candidates the one corresponding to the VQ encoder with the lowest encoder distortion. Two training methods are investigated: the generalized Lloyd algorithm and a non-iterative discrete cosine transform (DCT)-based approach.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Image Processing
PublisherIEEE Comp Soc
Pages751-755
Number of pages5
Volume3
Publication statusPublished - 1998
EventProceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3) - Chicago, IL, USA
Duration: Oct 4 1998Oct 7 1998

Other

OtherProceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3)
CityChicago, IL, USA
Period10/4/9810/7/98

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ASJC Scopus subject areas

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

Cite this

Panchapakesan, K., Sheppard, D. G., Marcellin, M. W., & Hunt, B. R. (1998). Blur identification from vector quantizer encoder distortion. In IEEE International Conference on Image Processing (Vol. 3, pp. 751-755). IEEE Comp Soc.