A. K. Katsaggelos*, J. Biemond, R. M. Mersereau, R. W. Schafer

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

41 Scopus citations


A general formulation of constrained iterative restoration algorithms is introduced in which deterministic and/or statistical information about the undistorted signal and statistical information about the noises are directly incorporated into the iterative procedure. This a priori information is incorporated into the restoration algorithm by what is called 'soft' or statistical constraints. Their effect on the solution depends on the amount of noise on the data; that is, the constraint operator is 'turned off' for noiseless data. The development of the new iterative algorithm is based on results from regularization techniques for stabilizing ill-posed problems.

Original languageEnglish (US)
Pages (from-to)700-703
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
StatePublished - Dec 1 1985

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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