To remove speckle noise in optical coherence tomography (OCT) images, the ProbShrink algorithm based on the dual-tree complex wavelet transform and a mixed probability model is employed. After studying the signal and noise distribution in OCT images, a mixed probability model in microscopic-level is introduced.
Logarithm of the OCT image is first decomposed using dual-tree complex wavelet transform. The coefficients consistent with edges obey the generalized Gaussian distribution, while others obey the Gaussian distribution. An improved ProbShrink algorithm is used to shrink the wavelet coefficients. Experiments show that this
method can significantly improve signal-to-noise ratio while hold edge preservation index relatively steady. The performance is better than that of traditional wavelet based OCT image denoising methods.