Noise adaptive wavelet thresholding for speckle noise removal in optical coherence tomography
Document Type
Article
Publication Date
5-1-2017
Abstract
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.
Identifier
85019016733 (Scopus)
Publication Title
Biomedical Optics Express
External Full Text Location
https://doi.org/10.1364/BOE.8.002720
e-ISSN
21567085
First Page
2720
Last Page
2731
Issue
5
Volume
8
Recommended Citation
Zaki, Farzana; Wang, Yahui; Su, Hao; Yuan, Xin; and Liu, Xuan, "Noise adaptive wavelet thresholding for speckle noise removal in optical coherence tomography" (2017). Faculty Publications. 9618.
https://digitalcommons.njit.edu/fac_pubs/9618