Nonlinear self-filtering of noisy images via dynamical stochastic resonance

Dmitry V. Dylov, Jason W. Fleischer

Research output: Contribution to journalArticlepeer-review

108 Scopus citations


From night vision and objects overwhelmed by sunlight to jammed signals and those that are purposely encrypted, detecting low-level or hidden signals is a fundamental problem in imaging. Here, we develop and exploit a new type of stochastic resonance, in which nonlinear coupling allows signals to grow at the expense of noise, to recover noise-hidden images propagating in a self-focusing medium. The growth rate is derived analytically by treating the signal-noise interaction as a photonic beam-plasma instability and matches experimentally measured resonances in coupling strength, noise statistics and modal content of the signal. This is the first observation of nonlinear intensity exchange between coherent and spatially incoherent light and the first demonstration of spatial coherence resonance for a dynamically evolving signal. The results suggest a general method of reconstructing images through seeded instability and confirm information limits predicted, but not yet observed, in nonlinear communications systems.

Original languageEnglish (US)
Pages (from-to)323-328
Number of pages6
JournalNature Photonics
Issue number5
StatePublished - May 2010

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics


Dive into the research topics of 'Nonlinear self-filtering of noisy images via dynamical stochastic resonance'. Together they form a unique fingerprint.

Cite this