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

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

doi:10.1364/boe.8.002720

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.

Highlights

Optical coherence tomography (OCT) is a high-speed, high resolution, three-dimensional imaging technique based on low coherence light interferometry [1]
Our noise adaptive wavelet thresholding (NAWT) algorithm utilized the characteristics of speckle noise in wavelet domain to adaptively remove speckle noise while preserving structure features in OCT image
Our results demonstrated that NAWT led to improved visual appearance of OCT image

Summary

Introduction

Optical coherence tomography (OCT) is a high-speed, high resolution, three-dimensional imaging technique based on low coherence light interferometry [1]. Speckle noise in OCT image randomly modulates the magnitude of OCT signal and obscures subtle image features, resulting in compromised effectiveness in its clinical applications [7, 8]. Hardware compounding for speckle noise reduction, such as spatial compounding and spectral compounding, may achieve higher signal to noise ratio (SNR) of OCT images, while compromise system cost, spatial resolution, and imaging speed [9,10,11]. Post-processing algorithms have been developed to reduce speckle noise in OCT images [12, 13]. Wavelet thresholding algorithms have demonstrated excellent capability in reducing speckle noise and preserving image sharpness [18, 19]. Our results clearly demonstrated the advantage of the NAWT algorithm compared to conventional wavelet domain thresholding and linear filtering

Principle

Results

Conclusion and discussion