Speckle denoising by the family of non-local means methods

Manoj Kumar, Yassine Tounsi, Abdelkrim Nassim, Fernando Mendoza-Santoyo, Osamu Matoba

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

1 Scopus citations

Abstract

We demonstrate the performance of nonlocal means (NLM) and its related adaptive kernel-based methods for speckle denoising for the intensity and phase images acquired from the digital speckle pattern interferometric (DSPI) and digital holographic interferometric (DHI) techniques, respectively. The speckle denoise capabilities of NLM and its variant denoising methods such as NLM-average (NLM-av), NLM-local polynomial regression (NLM-PLR), and NLM-shape adaptive patches (NLM-SAP), and various NLM-reprojection schemes are implemented on simulated. Their performances are quantified on the basis of two metric criteria - peak signal-to-noise ratio (PSNR) and the image quality index (Q). The effectiveness of these denoising methods is compared with other existing speckle denoising methods. The obtained results suggest that these denoising methods have the ability to denoise speckles from the DSPI/DHI fringes and provide better visual and quantitative results.

Original languageEnglish
Title of host publicationOptics, Photonics and Digital Technologies for Imaging Applications VI
EditorsPeter Schelkens, Tomasz Kozacki
PublisherSPIE
ISBN (Electronic)9781510634787
DOIs
StatePublished - 1 Jan 2020
Externally publishedYes
EventOptics, Photonics and Digital Technologies for Imaging Applications VI 2020 - Virtual, Online, France
Duration: 6 Apr 202010 Apr 2020

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11353
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceOptics, Photonics and Digital Technologies for Imaging Applications VI 2020
Country/TerritoryFrance
CityVirtual, Online
Period6/04/2010/04/20

Keywords

  • Digital holographic interferometry
  • Digital speckle pattern interferometer
  • Nonlocal means
  • Nonlocal means -reprojection schemes
  • Nonlocal means-average
  • Nonlocal means-local polynomial regression
  • Nonlocal means-shape adaptive patches
  • Speckle denoising

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