Noisy Image Enhancement Based on Three-state HMT Model in Wavelet domain
常霞 Chang Xia, 焦李成 JIAO Li-cheng, 贾建华 JIA Jian-hua, 辛芳芳 XIN Fang-fang, 万红林 WAN Hong-lin · ACTA PHOTONICA SINICA · 2010
A noisy image enhancement method is proposed based on the three-state hidden Markov tree model in wavelet domain.It is not need to confirm thresholds accurately,the three-state Gaussian mixture model is adopted to estimate the distribution of wavelets coefficients,according to the states posterior probability of each coefficient belongs to achieving by the training of expectation maximization algorithm,coefficients are distinguished into noise,weak edge and strong edge coefficients respectively.Then the enhanced noisy image is obtained by restraining noise coefficients and enhancing detail feature coefficients.Cycle spinning strategy is introduced to avoid visual artifacts.By experimenting on noisy standard images and brain magnetic resonance images,compared with several classical image enhancement methods in visual effects and quantitative analysis,experiments show that the enhancement method proposed bears better robustness,can emerge more detail information and restrain noise effectively at the same time.