Skip to main navigation Skip to search Skip to main content

Novel effective fuzzy diffusion algorithm for noise removal

  • School of Computer Science and Technology, Harbin Institute of Technology
  • Utah State University

Research output: Contribution to journalArticlepeer-review

Abstract

Anisotropic diffusion is widely used for noise reduction. The performance of anisotropic diffusion, in general, depends on the shape of the energy surface. The partial differential equation model is established and analyzed in the continuous domain while is implemented in the discrete domain. Therefore, the anisotropic diffusion bears some fuzziness due to the approximation. We present a novel noise removal algorithm based on fuzzy logic and anisotropic diffusion theory. The experimental results demonstrate that the proposed method has the advantage of maximizing noise reduction and preserving fine details of the images. In addition, the method can enhance the contrast of the images well.

Original languageEnglish
Article number127001
JournalOptical Engineering
Volume49
Issue number12
DOIs
StatePublished - Dec 2010
Externally publishedYes

Keywords

  • contrast enhancement
  • maximum entropy principle
  • noise removal
  • partial differential equation

Fingerprint

Dive into the research topics of 'Novel effective fuzzy diffusion algorithm for noise removal'. Together they form a unique fingerprint.

Cite this