A novel algorithm for color image denoising based on the CB color model

  • Fang Li*
  • *Corresponding author for this work

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

Abstract

In this paper, we propose a novel algorithm for color image denoising. The algorithm is based on Chromaticity-Brightness (CB) color model which separating the color image into two components: Chromaticity and brightness. The chromaticity is a unit vector on S2. Then the vectorial ROF model with unit norm constraint is used to process the chromaticity component. We first use Lagrange multipliers method to deal with the unit norm constraint, and derive the closed-form solution of Lagrange multipliers. Secondly, we add a new variable to substitute the chromaticity such that the original problem is split into two easier subproblems. One subproblem is minimizing the standard vectorial Rudin-Osher-Fatemi (ROF) model which can be solved by generalizing the Shen's fast operator splitting based scheme and the other has closed form solution. A number of experiments demonstrate that the proposed algorithm is effective in chromaticity and color image denoising.

Original languageEnglish
Title of host publication2013 IEEE Conference Anthology, ANTHOLOGY 2013
PublisherIEEE Computer Society
ISBN (Print)9781479916603
DOIs
StatePublished - 2013
Event2013 IEEE Conference Anthology, ANTHOLOGY 2013 - , China
Duration: 1 Jan 20138 Jan 2013

Publication series

Name2013 IEEE Conference Anthology, ANTHOLOGY 2013

Conference

Conference2013 IEEE Conference Anthology, ANTHOLOGY 2013
Country/TerritoryChina
Period1/01/138/01/13

Keywords

  • CB color model
  • alternating minimization
  • chromaticity
  • total variation

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