Image pretreatment tools I: Algorithms for map denoising and background subtraction methods

Carlo Vittorio Cannistraci, Massimo Alessio

Research output: Chapter in Book/Report/Conference proceedingChapter


One of the critical steps in two-dimensional electrophoresis (2-DE) image pre-processing is the denoising, that might aggressively affect either spot detection or pixel-based methods. The Median Modified Wiener Filter (MMWF), a new nonlinear adaptive spatial filter, resulted to be a good denoising approach to use in practice with 2-DE. MMWF is suitable for global denoising, and contemporary for the removal of spikes and Gaussian noise, being its best setting invariant on the type of noise. The second critical step rises because of the fact that 2-DE gel images may contain high levels of background, generated by the laboratory experimental procedures, that must be subtracted for accurate measurements of the proteomic optical density signals. Here we discuss an efficient mathematical method for background estimation, that is suitable to work even before the 2-DE image spot detection, and it is based on the 3D mathematical morphology (3DMM) theory.

Original languageEnglish
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Number of pages11
Publication statusPublished - 2016

Publication series

NameMethods in Molecular Biology
ISSN (Print)10643745


  • Background subtraction
  • Denoising
  • Image processing
  • Noise reduction filter
  • Spatial filtering
  • Two-dimensional gel electrophoresis

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics


Dive into the research topics of 'Image pretreatment tools I: Algorithms for map denoising and background subtraction methods'. Together they form a unique fingerprint.

Cite this