文件名称:PCANoiseLevelEstimator
- 所属分类：
- 图形图像处理(光照,映射..)
- 资源属性：
- [Matlab] [源码]
- 上传时间：
- 2017-03-15
- 文件大小：
- 2.75mb
- 下载次数：
- 0次
- 提 供 者：
- 陈**
- 相关连接：
- 无
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盲噪声估计出现在许多图像处理应用的问题，如去噪、COM压缩、分割。在本文中，我们提出了一种新的噪声电平估计方法的基础上的主成分分析的图像块。我们表明，噪声方差可以估计为图像块协方差矩阵的最小特征值。与现有的13种方法相比，所提出的方法显示了良好的速度和精度之间的妥协。这是至少15倍的速度比类似的精度的方法，它是至少两倍的精度比其他方法。我们的方法不假定存在均匀区域的输入图像，因此，可以成功地处理图像只包含纹理。-The problem of blind noise level estimation arises
in many image processing applications, such as denoising, com-
pression, and segmentation. In this paper, we propose a new
noise level estimation method on the basis of principal component
analysis of image blocks. We show that the noise variance can
be estimated as the smallest eigenvalue of the image block
covariance matrix. Compared with 13 existing methods, the
proposed approach shows a good compromise between speed
and accuracy. It is at least 15 times faster than methods with
similar accuracy, and it is at least two times more accurate
than other methods. Our method does not assume the existence
of homogeneous areas in the input image and, hence, can
successfully process images containing only textures.
in many image processing applications, such as denoising, com-
pression, and segmentation. In this paper, we propose a new
noise level estimation method on the basis of principal component
analysis of image blocks. We show that the noise variance can
be estimated as the smallest eigenvalue of the image block
covariance matrix. Compared with 13 existing methods, the
proposed approach shows a good compromise between speed
and accuracy. It is at least 15 times faster than methods with
similar accuracy, and it is at least two times more accurate
than other methods. Our method does not assume the existence
of homogeneous areas in the input image and, hence, can
successfully process images containing only textures.
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PCANoiseLevelEstimator.m
Image Noise Level Estimation by.pdf