An l1-TV Algorithm for Deconvolution with Salt and Pepper Noise

Abstract

There has recently been considerable interest in applying Total Variation regularization with an l1 data fidelity term to the denoising of images subject to salt and pepper noise, but the extension of this formulation to more general problems, such as deconvolution, has received little attention. We consider this problem, comparing the performance of l1- TV deconvolution, computed via our Iteratively Reweighted Norm algorithm, with an alternative variational approach based on Mumford-Shah regularization. The l1-TV deconvolution method is found to have a significant advantage in reconstruction quality, with comparable computational cost.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2009
Accession Number
ADA550706

Entities

People

  • Brendt Wohlberg
  • Paúl Rodríguez

Organizations

  • Los Alamos National Laboratory

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Computations
  • Digital Signal Processing
  • Gaussian Noise
  • Image Processing
  • Image Restoration
  • Information Operations
  • Inverse Problems
  • Mathematical Analysis
  • Noise
  • Signal Processing
  • Standards
  • Variational Principles
  • White Noise

Readers

  • Image Processing and Computer Vision.
  • Operations Research