Comparison of the main forms of half-quadratic regularization

Mila Nikolova*, Michael Ng

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

6 Citations (Scopus)

Abstract

We consider the reconstruction of images by minimizing regularized cost-functions. To accelerate the computation of the estimate, two forms of half-quadratic regularization, multiplicative and additive, are often used. The goal of this paper is to compare both theoretically and experimentally the efficiency of these two forms. We provide a theoretical and experimental analysis of the speed of convergence that they allow. We show that the multiplicative form gives rise to a better rate of convergence.

Original languageEnglish
Title of host publicationProceedings. International Conference on Image Processing, ICIP 2002
EditorsBillene Mercer
PublisherIEEE
PagesI/349-I/352
Number of pages4
ISBN (Print)0780376226
DOIs
Publication statusPublished - 22 Sept 2002
Event2002 International Conference on Image Processing, ICIP 2002 - Rochester, NY, United States
Duration: 22 Sept 200225 Sept 2002

Publication series

NameProceedings. International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference2002 International Conference on Image Processing, ICIP 2002
Country/TerritoryUnited States
CityRochester, NY
Period22/09/0225/09/02

Scopus Subject Areas

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

User-Defined Keywords

  • Regular Form
  • Convergence Rate
  • Right-hand Side
  • Cost Function
  • Invertible
  • Linear System
  • Proof Sketch
  • Form Of The Cost Function

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