Medical Image Denoising Based on Wavelet-Domain Hidden Markov Tree / 医疗卫生装备

ABSTRACT

Objective To denoise digital radiographic images well.Methods A technique was presented that used the Anscombe's transformation to adjust the original image to a Gaussian noise model based upon the wavelet denoising method and the wavelet-domain Hidden Markov Tree(HMT) model.Wavelet domain HMT models were used to determine the dependencies of multiscale wavelet coefficients through the state probabilities of the wavelet coefficients,whose sedistribution densities could be approximated by Gaussian mixture model.Results The proposed method could keep natural images edges from damaging and increase PSNR.Conclusion Quantitative and qualitative DR images assessment shows that the proposed algorithm outperforms the traditional Gaussian filter in terms of noise reduction,quality of details and bone sharpness.