Fast image and video denoising via nonlocal means of similar neighborhoods
Fast image and video denoising via nonlocal means of similar neighborhoods
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DOI：
10.1109/lsp.2005.859509
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发表时间：
2005-12-01
影响因子：
3.9
通讯作者：
Sapiro, G
中科院分区：
文献类型：
--
作者：
Mahmoudi, M;Sapiro, G
在这封信中，改进的非局部均值图像去噪方法介绍了布德斯等人。原始的非局部均值方法用具有相关周围邻域的像素的加权平均值来替换噪声像素。虽然产生最先进的去噪结果，但这种方法在计算上是不切实际的。为了加速算法，我们引入了过滤器，从加权平均值中消除不相关的邻域。这些滤波器是基于局部平均灰度值和梯度，预分类的邻域，从而减少了原来的二次复杂性的线性之一，并减少在一个给定的像素去噪的影响，相关性较低的地区。我们提出的基本框架和实验结果的灰度和彩色图像以及视频。
In this letter, improvements to the nonlocal means image denoising method introduced by Buades et al. are presented. The original nonlocal means method replaces a noisy pixel by the weighted average of pixels with related surrounding neighborhoods. While producing state-of-the-art denoising results, this method is computationally impractical. In order to accelerate the algorithm, we introduce filters that eliminate unrelated neighborhoods from the weighted average. These filters are based on local average gray values and gradients, preclassifying neighborhoods and thereby reducing the original quadratic complexity to a linear one and reducing the influence of less-related areas in the denoising of a given pixel. We present the underlying framework and experimental results for gray level and color images as well as for video.