Adaptive wavelet thresholding for optical coherence tomography image denoising

Farzana Zaki, Yahui Wang, Xin Yuan, Xuan Liu

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

2 Scopus citations

Abstract

For noise reduction in optical coherence tomography (OCT) image, wavelet domain thresholding has the unique advantage of suppressing noise while preserving image sharpness. However, previous applications of wavelet domain thresholding did not consider the fact that speckle noise has different characteristics in different spatial scales. In this study, we demonstrate a noise adaptive wavelet thresholding (NAWT) technology that exploits the difference in noise characteristics in different wavelet sub-bands. Our results demonstrated that NAWT outperforms conventional wavelet thresholding.

Original languageEnglish (US)
Title of host publicationComputational Optical Sensing and Imaging, COSI 2017
PublisherOSA - The Optical Society
ISBN (Electronic)9781557528209
DOIs
StatePublished - Jan 1 2017
EventComputational Optical Sensing and Imaging, COSI 2017 - San Francisco, United States
Duration: Jun 26 2017Jun 29 2017

Publication series

NameOptics InfoBase Conference Papers
VolumePart F46-COSI 2017

Other

OtherComputational Optical Sensing and Imaging, COSI 2017
CountryUnited States
CitySan Francisco
Period6/26/176/29/17

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Mechanics of Materials

Fingerprint Dive into the research topics of 'Adaptive wavelet thresholding for optical coherence tomography image denoising'. Together they form a unique fingerprint.

Cite this