Nonlocal Transform-Domain Filter for Volumetric Data Denoising and Reconstruction

@article{Maggioni2013NonlocalTF,
  title={Nonlocal Transform-Domain Filter for Volumetric Data Denoising and Reconstruction},
  author={Matteo Maggioni and Vladimir Katkovnik and Karen O. Egiazarian and Alessandro Foi},
  journal={IEEE Transactions on Image Processing},
  year={2013},
  volume={22},
  pages={119-133}
}
We present an extension of the BM3D filter to volumetric data. The proposed algorithm, BM4D, implements the grouping and collaborative filtering paradigm, where mutually similar d -dimensional patches are stacked together in a (d+1) -dimensional array and jointly filtered in transform domain. While in BM3D the basic data patches are blocks of pixels, in BM4D we utilize cubes of voxels, which are stacked into a 4-D “group.” The 4-D transform applied on the group simultaneously exploits the local… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-10 OF 190 CITATIONS, ESTIMATED 40% COVERAGE

190 Citations

02040'13'15'17'19
Citations per Year
Semantic Scholar estimates that this publication has 190 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
SHOWING 1-10 OF 35 REFERENCES

Brainweb: Simulated brain database

  • R. Vincent
  • http://mouldy.bic. mni.mcgill.ca/brainweb/, .
  • 2006
Highly Influential
4 Excerpts

Spatially adaptive filtering as regularization in inverse imaging: compressive sensing, upsampling, and super-resolution

  • A. Danielyan, A. Foi, V. Katkovnik, K. Egiazarian
  • Super-Resolution Imaging. CRC Press / Taylor…
  • 2010
Highly Influential
4 Excerpts

Similar Papers

Loading similar papers…