Constrained least-squares image restoration filters for sampled image data

Rajeeb Hazra, Stephen K. Park, G. Louis Smith, Stephen E. Reichenbach

Research output: Contribution to journalConference article

Abstract

Constrained least-squares image restoration, first proposed by Hunt twenty years ago, is a linear image restoration technique in which the smoothness of the restored image is maximized subject to a constraint on the fidelity of the restored image. The traditional derivation and implementation of the constrained least-squares restoration (CLS) filter is based on an incomplete discrete/discrete (d/d) system model which does not account for the effects of spatial sampling and image reconstruction. For many imaging systems, these effects are significant and should not be ignored. In a 1990 SPIE paper, Park et. al. demonstrated that a derivation of the Wiener filter based on the incomplete d/d model can be extended to a more comprehensive end-to-end, continuous/discrete/continuous (c/d/c) model. In a similar 1992 SPIE paper, Hazra et al. attempted to extend Hunt's d/d modelbased CLS filter derivation to the c/d/c model, but with limited success. In this paper, a successful extension of the CLS restoration filter is presented. The resulting new CLS filter is intuitive, effective and based on a rigorous derivation. The issue of selecting the user-specified inputs for this new CLS filter is discussed in some detail. In addition, we present simulation-based restoration examples for a FLIR (Forward Looking Infra-Red) imaging system to demonstrate the effectiveness of this new CLS restoration filter.

Original languageEnglish (US)
Pages (from-to)177-192
Number of pages16
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume2028
DOIs
StatePublished - Oct 20 1993
EventApplications of Digital Image Processing XVI 1993 - San Diego, United States
Duration: Jul 11 1993Jul 16 1993

Fingerprint

Constrained Least Squares
Image Restoration
Image reconstruction
Restoration
restoration
Filter
filters
derivation
Imaging System
Imaging systems
Wiener Filter
Infrared Imaging
Infrared imaging
Image Reconstruction
Discrete Model
Discrete Systems
Fidelity
Intuitive
Smoothness
image reconstruction

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

Constrained least-squares image restoration filters for sampled image data. / Hazra, Rajeeb; Park, Stephen K.; Louis Smith, G.; Reichenbach, Stephen E.

In: Proceedings of SPIE - The International Society for Optical Engineering, Vol. 2028, 20.10.1993, p. 177-192.

Research output: Contribution to journalConference article

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