Diffusion reconstruction from very noisy tomographic data
Diffusion reconstruction from very noisy tomographic data
复制标题
从非常嘈杂的断层扫描数据进行扩散重建
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
A. Louis
中科院分区：
文献类型：
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作者：
A. Louis
由于层析数据噪声很大，重建图像受到严重放大的噪声污染。通常会考虑两种补救措施。首先对数据进行平滑处理，这在工程文献中称为预白化。这里的缺点是单独处理的数据集可能变得不一致。其次，对原始数据集重构后的图像进行平滑处理；作为例子，提到了扩散滤波器。本文提出了一种一步重建平滑图像的方法；也就是说，我们开发了特殊的重建核，它直接计算经过扩散滤波器平滑的图像。给出了合成数据的实例。
As a consequence of very noisy tomographic data the reconstructed images are contaminated by severely amplified noise. Typically two remedies are considered. Firstly, the data are smoothed, this is called pre-whitening in the engineering literature. The disadvantage here is that the individually treated data sets could become inconsistent. Secondly, the image, reconstructed from the original data sets, is treated by methods of image smoothing. As example diffusion filters are mentioned. In this paper we present a method where the reconstruction of the smoothed image is performed in one step; i.e., we develop special reconstruction kernels, which directly compute the image smoothed by a diffusion filter. Examples from synthetic data are presented.