Wavelet tree structure based speckle noise removal for optical coherence tomography

Xin Yuan; Xuan Liu; Yang Liu

doi:10.1117/12.2290760

14 February 2018 Wavelet tree structure based speckle noise removal for optical coherence tomography

Xin Yuan, Xuan Liu, Yang Liu

Proceedings Volume 10483, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXII; 104832Q (2018) https://doi.org/10.1117/12.2290760
Event: SPIE BiOS, 2018, San Francisco, California, United States

Abstract

We report a new speckle noise removal algorithm in optical coherence tomography (OCT). Though wavelet domain thresholding algorithms have demonstrated superior advantages in suppressing noise magnitude and preserving image sharpness in OCT, the wavelet tree structure has not been investigated in previous applications. In this work, we propose an adaptive wavelet thresholding algorithm via exploiting the tree structure in wavelet coefficients to remove the speckle noise in OCT images. The threshold for each wavelet band is adaptively selected following a special rule to retain the structure of the image across different wavelet layers. Our results demonstrate that the proposed algorithm outperforms conventional wavelet thresholding, with significant advantages in preserving image features.

Citation Download Citation

Xin Yuan, Xuan Liu, and Yang Liu "Wavelet tree structure based speckle noise removal for optical coherence tomography", Proc. SPIE 10483, Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXII, 104832Q (14 February 2018); https://doi.org/10.1117/12.2290760

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