Diffusion interpretation of nonlocal neighborhood filters for signal denoising

Amit Singer, Yoel Shkolnisky, Boaz Nadler

Research output: Contribution to journalArticlepeer-review

74 Scopus citations


Nonlocal neighborhood filters are modern and powerful techniques for image and signal denoising. In this paper, we give a probabilistic interpretation and analysis of the method viewed as a random walk on the patch space. We show that the method is intimately connected to the characteristics of diffusion processes, their escape times over potential barriers, and their spectral decomposition. In particular, the eigenstructure of the diffusion operator leads to novel insights on the performance and limitations of the denoising method, as well as a proposal for an improved filtering algorithm.

Original languageEnglish (US)
Pages (from-to)118-139
Number of pages22
JournalSIAM Journal on Imaging Sciences
Issue number1
StatePublished - 2009

All Science Journal Classification (ASJC) codes

  • General Mathematics
  • Applied Mathematics


  • Denoising
  • First passage time
  • Fokker-planck equation
  • Neighborhood filters
  • Nonlocal means


Dive into the research topics of 'Diffusion interpretation of nonlocal neighborhood filters for signal denoising'. Together they form a unique fingerprint.

Cite this