Application of threshold estimation for terahertz digital holography image denoising based on stationary wavelet transform

摘要

Terahertz digital holography imaging technology is one of the hot topics in imaging domain, and it has drawn more and more public attention. Owing to the redundancy and translation invariance of the stationary wavelet transform, it has significant application in image denoising, and the threshold selection has a great influence on denoising. The denoising researches based on stationary wavelet transform are performed on the real terahertz image, with Bayesian estimation and Birge-Massart strategy applied to evaluate the threshold. The experimental results reveal that, Bayesian estimation combined with homomorphic stationary wavelet transform manifests the optimal denoising effect at 3 decomposition levels, which improves the signal-to-noise and preserves the image detail information simultaneously.