摘要
研究了图像处理中各向异性扩散的正则化参数选取问题.根据分片常数模型,提出了一种噪声估计方法,该方法通过寻找图像中的最小区域方差来估计噪声;分析了正则化参数与图像噪声的关系,提出了一个正则化参数选取的修正公式,该公式使正则化参数能根据图像噪声自适应调整;最后给出了由正则化参数选取高斯模板尺度的规则.实验结果显示,这种正则化选取方法可以使各向异性扩散方程对图像噪声具有很好的自适应性.
The selection of regularization parameter for anisotropic diffusion in image processing is discussed. An approach of noise estimation based piecewise constant image model is proposed. In this approach,image noise is estimated by minimal variance of region in image. And then the relation between regularization parameter and image noise is analyzed. A modified formula between regularization parameter and image noise is suggested. According to this formula, regularization parameter is adapted to image noise. Finally, the rule to select size of gauss mask to regularization parameter is given. Resutt shows that anisotropic diffusion have good adaptability to image noise with the selection of regularization parameter.
出处
《光子学报》
EI
CAS
CSCD
北大核心
2005年第9期1411-1414,共4页
Acta Photonica Sinica
基金
高等学校博士学科点专项科研基金(No.20020699014)
航天科技创新基金(No.N4CH0008)
关键词
各向异性扩散
分片常数模型
正则化参数
噪声估计
Anisotropic diffusion
Piecewise constant model
Regularization parameter
Noise estimation
