摘要
从小波变换入手 ,提出了一种概率自适应去噪模型 .该模型包括尺度层间模型和层内模型 .去噪方法首先利用小波域层间模型 ,将小波系数分成两类 :有意义系数和无意义系数 ;然后在层内概率模型下运用最大后验概率估计方法 ,从有意义系数中恢复出原始系数 .我们还将这种模型引入复数小波变换域 .实验结果及分析表明了该去噪模型的有效性 .
A probability model for adaptive image denoising based on the wavelet transform is proposed.The new model includes an interscale model and an intrascale model.Firstly,we use the interscale model to classify the coefficients into two classes: significant coefficients and insignificant coefficients.Secondly,the maximum a posteriori (MAP) estimator based on the intrascale model is used to restore the noisy wavelet image coefficients.The same model can be applied to the complex wavelet domain.Experimental results and analysis are given to demonstrate the validity and effectiveness of the proposed model.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2005年第1期63-66,共4页
Acta Electronica Sinica
关键词
小波变换
图像去噪
复数小波变换
最大后验概率
wavelet transform
image denoising
complex wavelet transform (CWT)
maximum a posteriori (MAP)
