Noise adaptive wavelet thresholding for speckle noise removal in optical coherence tomography

Farzana Zaki, Yahui Wang, Hao Su, Xin Yuan, Xuan Liu

Research output: Contribution to journalArticlepeer-review

73 Scopus citations


Optical coherence tomography (OCT) is based on coherence detection of interferometric signals and hence inevitably suffers from speckle noise. To remove speckle noise in OCT images, wavelet domain thresholding has demonstrated significant advantages in suppressing noise magnitude while preserving image sharpness. However, speckle noise in OCT images has different characteristics in different spatial scales, which has not been considered in previous applications of wavelet domain thresholding. In this study, we demonstrate a noise adaptive wavelet thresholding (NAWT) algorithm that exploits the difference of noise characteristics in different wavelet sub-bands. The algorithm is simple, fast, effective and is closely related to the physical origin of speckle noise in OCT image. Our results demonstrate that NAWT outperforms conventional wavelet thresholding.

Original languageEnglish (US)
Pages (from-to)2720-2731
Number of pages12
JournalBiomedical Optics Express
Issue number5
StatePublished - May 1 2017

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Atomic and Molecular Physics, and Optics


  • Image reconstruction restoration
  • Noise in imaging systems
  • Optical coherence tomography
  • Speckle


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