MMSE nonlocal means denoising algorithm for Poisson noise removal

Chul Lee, Chulwoo Lee, Chang-Su Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

A nonlocal minimum mean square error (MMSE) image denoising algorithm to remove Poisson noise is proposed in this work. Based on the Bayesian estimation theory, we first derive the nonlocal MMSE denoising filter, which can minimize the mean square error (MSE) of a denoised block. Then, we develop an approximation of the filter for practical implementation. Simulation results show that the proposed algorithm provides significantly better denoising performance than the conventional nonlocal means filter and its recent extension for Poisson noise.

Original languageEnglish
Title of host publicationICIP 2011
Subtitle of host publication2011 18th IEEE International Conference on Image Processing
Pages2561-2564
Number of pages4
DOIs
Publication statusPublished - 2011
Event2011 18th IEEE International Conference on Image Processing, ICIP 2011 - Brussels, Belgium
Duration: 2011 Sep 112011 Sep 14

Publication series

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

Other

Other2011 18th IEEE International Conference on Image Processing, ICIP 2011
CountryBelgium
CityBrussels
Period11/9/1111/9/14

Keywords

  • Bayesian estimation
  • Image denoising
  • MMSE denoising
  • Poisson noise
  • nonlocal means (NLM) filter

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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