Infrared Image Denoising Method Based on Improved C_HMT Model

摘要：

Contourlet coefficients are modeled using a hidden Markov tree (HMT) model with Gaussian mixtures that can capture all interscale,interdirection,and interlocation dependencies,which is more valid than wavelet HMT model.Put forward an improved contourlet-domain hidden Markov tree model where the state of the contourlet coefficients depends not only on the state of its parent node but on the state of the twin of its parent as well.This strategy can catch richer interscale correlation of the contourlet coefficient,and then is more suitable for representing non-Gaussian statistics and persistence of the contourlet coefficient.The improved model is used in infrared image denoising and compared with the other denoising method,such as wavelet threshold and wavelet HMT,and the simulation results show the method is more advantage restoring edges of original image.

作者: Ming Cheng Xue Mei Jinguo Lin Liang Wang

会议类型: 国际会议

会议名称: Asia Simulation Conference 2008/the 7th International Conference on System Simulation and Scientific Computing(2008亚洲仿真会议/第七届系统仿真和科学计算国际会议)(ICSC2008)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-10（万方平台首次上网日期，不代表论文的发表时间）