摘要
提出了一种基于小波变换和数据融合技术的图像降噪的方法 .此方法对同一原始图像信号不同噪声的多源图像分别进行小波分解 ,在图像分解的高频域内 ,对小波系数进行阈值处理后 ,再进行数据融合处理 ,根据 "多数原则 "选择重要小波系数 .在低频域内 ,新的逼近系数则通过对多幅图像的逼近系数直接进行加权平均得到 .然后利用重要小波系数和逼近系数进行小波反变换 ,即可得到融合后的图像 .实验结果表明 :此方法既可以有效地降低噪声 。
A Method of image noise reduction based on wavelet transform and data fusion is proposed.With this method,several images including same original signal and different noises are decomposed by wavelet transform,In high frequency area, the coefficients is transacted by thresholding operation,and then important wavelet coefficients are selected according by 'majority principle's ; In low frequency, the new approximation coefficients is obtained directly by the weightened mean value of the defficients in different images.And the fused image can be obtained by using the inverse wavelet transform for all important coefficients and approximation coefficients. Experimental results show:using this method , image noise can be reduced effectively, and little image detail is lossed at the same time.
出处
《小型微型计算机系统》
CSCD
北大核心
2004年第5期896-899,共4页
Journal of Chinese Computer Systems
基金
湖南省教育厅科研项目 ( 0 3 B0 3 3 )资助
关键词
小波变换
数据融合
图像噪声
wavelet transform
data fusion
image noise
