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http://yadda.icm.edu.pl:80/baztech/element/bwmeta1.element.baztech-article-BAT5-0006-0067

Czasopismo

Image Processing & Communications

Tytuł artykułu

Reconstruction of digital images from their instantaneous mixtures by the blind source separation algorithms

Autorzy Adhami, R.  Janik, T. 
Treść / Zawartość http://content.sciendo.com/view/journals/ipc/ipc-overview.xml
Warianty tytułu
Języki publikacji EN
Abstrakty
EN The goal of the blind source separation (BSS) is to recover independent sources from the sensor observation which are unknown linear mixtures of the unobserved source signals. In contrast to correlation-based transformation such as the principal component analysis, the blind techniques not only decorrelate the signals (second-order statistics) but also reduce higher-order dependencies, attempting to make the signals as independent as possible. In this paper we introduce the BSS algorithms with the emphasis on applications in image processing. Computer simulations illustrate and confirm the usefulness and performance of the discussed algorithms.
Słowa kluczowe
PL separacja źródła błędu   analiza niezależnych komponentów   przetwarzanie obrazów  
EN blind source separation   independent component analysis   image processing  
Wydawca Instytut Telekomunikacji Uniwersytetu Technologiczno-Przyrodniczego w Bydgoszczy
Czasopismo Image Processing & Communications
Rocznik 2005
Tom Vol. 10, no 1
Strony 35--42
Opis fizyczny Bibliogr. 11 poz., rys., wykr.
Twórcy
autor Adhami, R.
  • University of Alabama in Huntsville Department of Computer and Electrical Engineering Huntsville, AL 35899, USA, rradhami@ece.uah.edu
autor Janik, T.
Bibliografia
[1] J.-F. Cardoso, A. Souloumiac, Jacob! angles for simultaneous diagonalization, SIAM Journal on Matrix Analysis and Applications, 17, 1996, 161-164.
[2] A. Cichocki, S. Amari, Adaptive Blind Signal and Image Processing. Learning Algorithms and Applications, New York, NY, Wiley, 2002.
[3] A. Cichocki, S. Amari, K. Siwek, et al., ICALAB Toolboxes, http://www.bsp.brain.riken.go.jp/ICALAB.
[4] A. Cichocki, L. Moszczynski, A new learning algorithm for blind separation of sources, Electronics Letters, 28, 1992, 1986-1987.
[5] S. Douglas, Blind signal separation: an overview of density-based methods, Proc. International Workshop on Acoustic Echo and Noise Control, Pocono Manor, PA, 1999, 8-11.
[6] R. Gonzalez, R. Woods, Digital Image Processing, Reading, MA, Addison-Wesley, 1992.
[7] S. Haykin (Ed.), Unsupervised Adaptive Filtering. Volume I: Blind Source Separation, New York, NY, Wiley, 2000).
[8] A. Hyvarinen, J. Karhunen, E. Oja, Independent Component Analysis, New York, NY: Wiley, 2001.
[9] A. Jain, Fundamentals of Digital Image Processing, Englewood Cliffs, NJ, Prentice Hall, 1989.
[10] C. Jutten, Source separation: from dusk till dawn, Proc. 2nd Int. Workshop on ICA and BSS (ICA 2000), Helsinki, Finland, 2000, 15-26.
[11] S. Roberts, R. Everson (Eds.), Independent Component Analysis. Principle and Practice, Cambridge, MA: University Press, 2001.
Kolekcja BazTech
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