Multi-parameter regularization methods for high-resolution image reconstruction with displacement errors

Yao Lu, Lixin Shen, Yuesheng Xu

Research output: Contribution to journalArticle

24 Scopus citations

Abstract

We propose multi-parameter regularization methods for high-resolution image reconstruction which is described by an ill-posed problem. The regularization operator for the ill-posed problem is decomposed in a multiscale manner by using bi-orthogonal wavelets or tight frames. In the multiscale framework, for different scales of the operator we introduce different regularization parameters. These methods are analyzed under certain reasonable hypotheses. Numerical examples are presented to demonstrate the efficiency and accuracy of these methods.

Original languageEnglish (US)
Pages (from-to)1788-1799
Number of pages12
JournalIEEE Transactions on Circuits and Systems I: Regular Papers
Volume54
Issue number8
DOIs
StatePublished - Aug 1 2007

Keywords

  • Framelets
  • High-resolution image reconstruction
  • Multi-parameter regularization
  • Wavelets

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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