在本文中，我们专注于为添加剂和多折扇状的模型提出了一种简单而新颖的方法为此自动噪声参数估计问题。我们表明，如果图像的工作有一个足够大的量的变异率低的地区（这是一个典型的在大多数图像的特征），噪声的方差（如果添加剂）可作为估计的分布模式在图像局部方差的分布与变化噪声系数（如果乘法）可以估计的变异系数局部估计的分布模式。此外，模型的样本方差分布的图像加噪声的建议和研究。实验表明，所提出的方法的优点，特别是在递归或迭代滤波方法。-In this paper, we focus on the problem of automatic noise parameter estimation for additive and multi-

plicative models and propose a simple and novel method to this end. Specifically we show that if the

image to work with has a sufficiently great amount of low-variability areas (which turns out to be a typ-

ical feature in most images), the variance of noise (if additive) can be estimated as the mode of the dis-

tribution of local variances in the image and the coefficient of variation of noise (if multiplicative) can be

estimated as the mode of the distribution of local estimates of the coefficient of variation. Additionally, a

model for the sample variance distribution for an image plus noise is proposed and studied. Experiments

show the goodness of the proposed method, specially in recursive or iterative filtering methods.