Please find the respective information in the following paper.

Qureshi,H., Malik,M., Ahmad,M.A., Heinzl,C.: “Benchmarking of De-noising Techniques for Streaking Artifacts in Industrial 3DXCT Scan Data” (http://www.wscg.eu/)

Abstract:
De-noising is one of the most important applications of
image processing, which has found application in a wide
variety of domains. De-noising allows for improving
image quality in noise prone imaging modalities.
Although, de-noising has been applied rigorously in 2D
imaging, but new modalities of imaging such as industrial
3D X-ray computed tomography (3DXCT) have not
received much attention. Industrial XCT scanning is used
today to acquire images of industrial components and
machinery so that defects within these can be identified
non-destructively and non-intrusively. However, the main
problem in XCT is that XCT imaging is prone to artifacts
and noise in the generated data. One solution to the
problem is the increased number of projections which
results in reduced noise but leads to increased cost. In
this paper, we show how various de-noising techniques
may be used to de-noise 3DXCT scan images. We also
benchmark these techniques using various picture quality
measures. Our investigation shows that high quality
results may be obtained using wavelet shrinkage and
anisotropic diffusion.