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Application of Backward Stochastic Differential Equations to Reconstruction of Vector-Valued Images

  • Dariusz Borkowski
  • Katarzyna Jańczak-Borkowska
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7594)

Abstract

In this paper we explore the problem of reconstruction of vector-valued images with additive Gaussian noise. In order to solve this problem we use backward stochastic differential equations. Our numerical experiments show that the new approach gives very good results and compares favourably with deterministic partial differential equation methods.

Keywords

Wiener Process Noisy Image Image Quality Assessment Additive Gaussian Noise IEEE Signal Processing Magazine 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Dariusz Borkowski
    • 1
  • Katarzyna Jańczak-Borkowska
    • 2
  1. 1.Faculty of Mathematics and Computer ScienceNicolaus Copernicus UniversityToruńPoland
  2. 2.Institute of Mathematics and PhysicsUniversity of Technology and Life SciencesBydgoszczPoland

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