基于混合噪声模型的射线图像降噪方法  

Multi-noise Model-based Denoising Method for Radiographic Image

作　　者：申清明[1] 王国博[1] 赵建中[1] 许管利[1] 

机构地区：[1]西北机电工程研究所,陕西咸阳712099

出　　处：《兵工学报》2014年第12期2087-2091,共5页Acta Armamentarii

摘　　要：针对射线数字图像的特点,提出了一种基于混合噪声模型的小波中值滤波降噪方法。对射线数字图像噪声成分构成进行分析,建立了混合噪声模型。根据混合噪声模型来计算噪声方差,进而计算Bayes Shrink阈值,解决了Bayes Shrink阈值计算中因射线数字图像小波系数不服从广义高斯分布而导致的Donoho噪声方差计算方法失效的问题。为了消除Bayes Shrink阈值处理引起的图像失真,对小波阈值处理结果进行中值滤波。采用射线数字图像对该方法的有效性进行了验证,实验表明,该方法的降噪效果优于Oracle Shrink和Sure Shrink阈值法。A multi-noise model-based denoising method for radiographic image is proposed,in which wavelet transform and median filtering are used.The composition of the image noise is analyzed,and a multi-noise model is established.The variance of noise is calculated in terms of the multi-noise model,and then the BayesShrink threshold is calculated,which solves the problem of that the Donoho＇ s noise algorithm is invalidated since the wavelet coefficients do not obey the generalized Gaussian distribution.A median filtering is used to refine the result obtained by the wavelet transform to eliminate the image distortion caused by the BayesShrink thresholding.Radiographic images are used to verify the effectiveness of the proposed method.Experiments show that the performance of the proposed method is better than those of OracleShrink and SureShrink.

关 键 词：信息处理技术 混合噪声模型 小波 图像降噪 

分 类 号：TN911.7[电子电信—通信与信息系统]