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首页> 外文会议>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）(ICSC'2008)论文集 >Infrared Image Denoising Method Based on Improved C_HMT Model
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Infrared Image Denoising Method Based on Improved C_HMT Model

机译：基于改进C_HMT模型的红外图像降噪方法

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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.
机译：Contourlet系数是使用隐马尔可夫树（HMT）模型与高斯混合模型进行建模的，该模型可以捕获所有尺度间，相互间和位置相关性，比小波HMT模型更有效。提出了一种改进的Contourlet域隐马尔可夫树模型Contourlet系数的状态不仅取决于其父节点的状态，还取决于其父节点的孪生子的状态。此策略可以捕获Contourlet系数的更丰富的尺度间相关性，然后更适合表示非高斯改进后的模型用于红外图像去噪，并与小波阈值和小波HMT等其他去噪方法进行了比较，仿真结果表明该方法在恢复原始图像边缘方面更具优势。

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