摘要
提出了一种自适应权值滤波算法。该方法利用邻域差分法(ROAD)判定滤波中心点的有效性,若判定该点为噪声,则将邻域像素分别赋予不同权值对该点像素重构,邻域像素权重系数的分配随该点有效程度的增加而增大。一方面抑制了图像噪声,另一方面保留了图像细节。实验证明该方法在滤除椒盐噪声时,无论从视觉角度还是数据恢复角度都比常规滤波方法效果有明显改善。当图像中含有35%的椒盐噪声时,利用该方法恢复数据效果比传统中值滤波提高10 dB。
An auto-adapted weight filtering method is put forward. The validity of the pixel is analyzed with a Rank-order Absolute Difference （ROAD） method, if the pixel is noise, the pixel will be reconstructed by the neighbor pixels with different weights, and the weight of the neighbor pixel is correlative with its validity. At last, not only the impulse noise is restrained, but also the detail of the image is reserved. Experiments show that when using the auto-adapted weight filtering to get rid of the impulse noise, an evident improvement is found compared with the general method, both in visual image quality and quantitative measures of signal restoration. When the impulse noise occupies 35% in image, the effect of data recovery by this method can be increased by 10 dB compared with conventional median filter.
出处
《光学精密工程》
EI
CAS
CSCD
北大核心
2007年第5期779-783,共5页
Optics and Precision Engineering
基金
国家高技术研究发展计划基金资助项目(No.2006AA703405F)
关键词
图像消噪
椒盐噪声
邻域绝对值差分法
自适应权值滤波
image denoising
impulse noise
rank-order absolute difference
auto-adapted weight filter
