An image processing approach for underdetermined blind separation of nonstationary sources

  • K. Abed-Meraim
  • , N. Linh-Trung
  • , V. Sucic
  • , F. Tupin
  • , B. Boashash

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a new approach for blind separation of nonstationary frequency-modulated (FM) sources in the underdetermined case (i.e., more sources than sensors) using their time-frequency distributions (TFDs). The underlying idea of the proposed blind source separation (BSS) method is based on the observation that a monocomponent FM signal is represented by a linear feature corresponding to the 'energy concentration points' in the time-frequency (TF) image. Therefore, we propose to adapt an existing 'road network extraction' method [Tupin et al., (1998)] for the detection and separation of the source signal components from the spatially averaged TF image of their mixtures. The sources spatial signatures are then used to group together (classify) the components of the same source (or equivalently, the same spatial direction). Simulation examples are provided to assess the performance of the proposed algorithm in various scenarios.

Original languageEnglish
Title of host publicationISPA 2003 - Proceedings of the 3rd International Symposium on Image and Signal Processing and Analysis
EditorsA. Neri, H. Babic, S. Loncaric
PublisherIEEE Computer Society
Pages347-352
Number of pages6
ISBN (Electronic)953184061X
DOIs
Publication statusPublished - 1 Jan 2003
Event3rd International Symposium on Image and Signal Processing and Analysis, ISPA 2003 - Rome, Italy
Duration: 18 Sept 200320 Sept 2003

Publication series

NameInternational Symposium on Image and Signal Processing and Analysis, ISPA
Volume1
ISSN (Print)1845-5921
ISSN (Electronic)1849-2266

Conference

Conference3rd International Symposium on Image and Signal Processing and Analysis, ISPA 2003
Country/TerritoryItaly
CityRome
Period18/09/0320/09/03

Keywords

  • Array signal processing
  • Blind source separation
  • Clustering algorithms
  • Image processing
  • Image sensors
  • Signal processing
  • Signal processing algorithms
  • Source separation
  • Telecommunications
  • Time frequency analysis

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