Spatially-variant roughness penalty design for uniform resolution in penalized-likelihood image reconstruction

J. Webster Stayman, Jeffrey A. Fessler

Research output: Contribution to conferencePaperpeer-review

Abstract

Traditional space-invariant regularization schemes in tomographic image reconstruction using penalized-likelihood estimators produce images with nonuniform resolution properties. The local point spread functions that quantify the local smoothing properties of such estimators are not only space-variant and asymmetric, but are also object-dependent even for space-invariant systems. We propose a new regularization scheme for increased spatial uniformity and demonstrate the resolution properties of this new method versus conventional regularization schemes through an investigation of local point spread functions.

Original languageEnglish (US)
Pages685-689
Number of pages5
StatePublished - Dec 1 1998
Externally publishedYes
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

ASJC Scopus subject areas

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

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