机构

• 自动化研究所 [2]
• 长春光学精密机械与物... [1]

采集方式

• OAI收割 [3]

内容类型

• 期刊论文 [2]
• 会议论文 [1]

发表日期

• 2017 [1]
• 2016 [1]
• 2006 [1]

学科主题

筛选

浏览/检索结果: 共3条，第1-3条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序提交时间升序提交时间降序作者升序作者降序发表日期升序发表日期降序 Image Deno sing via Multiscale Nonlinear Diffusion Models 期刊论文  OAI收割 SIAM JOURNAL ON IMAGING SCIENCES, 2017, 卷号: 10, 期号: 3, 页码: 1234-1257 作者:  Feng, Wensen;  Qiao, Peng;  Xi, Xuanyang;  Chen, Yunjin   |  收藏  |  浏览/下载：37/0  |  提交时间：2018/03/03 Image Denoising  Multiscale Pyramid Image Representation  Trainable Nonlinear Reaction Diffusion Model  Gaussian Denoising  Poisson Denoising   Poisson Noise Reduction with Higher-Order Natural Image Prior Model 期刊论文  OAI收割 SIAM JOURNAL ON IMAGING SCIENCES, 2016, 卷号: 9, 期号: 3, 页码: 1502-1524 作者:  Feng, Wensen;  Qiao, Hong;  Chen, Yunjin 收藏  |  浏览/下载：29/0  |  提交时间：2016/12/05 Poisson denoising  fields of experts  Anscombe root transformation  nonconvex optimization   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：18/0  |  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.