X-Ray Image Denoising using Multivariate Shrinkage Function in Wavelet Domain

Abstract

The distortion of medical images by noise is common during its processing and transmission. So, this research is concerned with wavelet-based X-ray image denoising using Bayesian techniques. Indeed, one of the cruxes of the Bayesian image denoising algorithms is to estimate the local variance of the image. Here, we employ maximum a posterior (MAP) estimation to calculate local observed variance with Pareto distribution prior for local observed variance and Laplacian or Gaussian distribution for noisy wavelet coefficients.