The use of levelable regularization functions for MRF restoration of SAR images while preserving reflectivity

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

It is well-known that Total Variation (TV) minimization with L2 data fidelity terms (which corresponds to white Gaussian additive noise) yields a restored image which presents some loss of contrast. The same behavior occurs for TV models with non-convex data fidelity terms that represent speckle noise. In this note we propose a new approach to cope with the restoration of Synthetic Aperture Radar images while preserving the contrast.

Original languageEnglish
Title of host publicationProceedings of SPIE-IS and T Electronic Imaging - Computational Imaging V
DOIs
Publication statusPublished - 31 Aug 2007
EventComputational Imaging V - San Jose, CA, United States
Duration: 29 Jan 200731 Jan 2007

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6498
ISSN (Print)0277-786X

Conference

ConferenceComputational Imaging V
Country/TerritoryUnited States
CitySan Jose, CA
Period29/01/0731/01/07

Keywords

  • Energy minimization
  • Image restoration
  • Levelable functions
  • Synthetic aperture Radar
  • Total variation

Fingerprint

Dive into the research topics of 'The use of levelable regularization functions for MRF restoration of SAR images while preserving reflectivity'. Together they form a unique fingerprint.

Cite this