Medical Image Denoising Based on Wavelet-Domain Hidden Markov Tree
- VernacularTitle:基于小波域隐马尔可夫树模型的医学图像去噪
- Author:
Wei FU
;
Hongxiao WAN
;
Gang TU
- Publication Type:Journal Article
- Keywords:
wavelet transform;
wavelet-domain hidden markov tree model;
Anscombe's transformation;
image denoising;
gauss noise
- From:
Chinese Medical Equipment Journal
1989;0(01):-
- CountryChina
- Language:Chinese
-
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.
