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Sequential data feature selection for human motion recognition via Markov blanket 期刊论文  OAI收割
Pattern Recognition Letters, 2017, 卷号: 86
作者:  Zhou, H.;  M. You;  L. Liu and C. Zhuang
  |  收藏  |  浏览/下载：9/0  |  提交时间：2018/06/13
CR image filter methods research based on wavelet-domain hidden markov models (EI CONFERENCE) 会议论文  OAI收割
ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China
作者:  Wang J.-L.;  Wang J.-L.;  Li D.-Y.;  Wang Y.-P.
收藏  |  浏览/下载：13/0  |  提交时间：2013/03/25
In the procedure of computed radiography imaging  we should firstly get across the characters of kinds of noises and the relationship between the image signals and noises. Based on the specialties of computed radiography (CR) images and medical image processing  we have study the filtering methods for computed radiography images noises. On the base of analyzing computed radiography imaging system in detail  the author think that the major two noises are Gaussian white noise and Poisson noise. Then  the different relationship of between two kinds of noises and signal were studied completely. By considering both the characteristics of computed radiography images and the statistical features of wavelet transformed images  a multiscale image filtering algorithm  which based on two-state hidden markov model (HMM) and mixture Gaussian statistical model  has been used to decrease the Gaussian white noise in computed images. By using EM (Expectation Maximization) algorithm to estimate noise coefficients in each scale and obtain power spectrum matrix  then this carried through the syncretized two Filter that are IIR(infinite impulse response) Wiener Filter and HMM  according to scale size  and achieve the experiments as well as the comparison with other denoising methods were presented at last.