Research Article
Optical Coherence Tomography Noise Reduction Using Anisotropic Local Bivariate Gaussian Mixture Prior in 3D Complex Wavelet Domain
Algorithm 1
Outline of the proposed denoising algorithm.
Summarization of the proposed denoising algorithm | Step 1. Complex Wavelet Transformation of Noisy Image to Find and . | Step 2. Estimation of the Prior (Finding Mixture Model Parameters in Each Subband). | 2.1. Initialization for a(k) and . | 2.2. Using (34) to find . | 2.3. Using (37) to update a(k) by substituting from Step 2.2. | 2.4. Updating the parameters of prior, , using (36) and (37). | 2.5. Finding from (27) for AWGN and (28) for two-sided Rayleigh noise using updated | value in Step 2.3. | 2.6. Iteration Step 2.2 to 2.4 until parameter convergence. | Step 3. Substituting the Final Parameters in Step 2 in Shrinkage Function (30) for AWGN | (after obtaining using (31)) and Shrinkage Function (32) for two-sided Rayleigh | noise (after obtaining using (33)). | Step 4. Inverse Complex Wavelet Transformation. |
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