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Master STIC - Specialization :Computational Biology

Deconvolution and denoising for confocal microscopy

Faculty : Josiane Zerubia, (INRIA-Ariana) and Laure Blanc-Féraud (CNRS-Ariana)
Course location : Polytech' Nice-Sophia French engineering school from Nice Sophia Antipolis University
Description :

  • This course is concerned with the presentation of basic and advanced models and algorithms for confocal microscopy. First an introduction to confocal microscopes will be done, including the description of the various types of noises and point spread functions (PSF). Then, a brief overview about sampling theory, convolution and inverse filtering will be conducted, followed by the description of the basic restoration and deconvolution techniques proposed in the literature using either variational or Markovian models. Various confocal microscopy deconvolution methods will be introduced (using the L1 or L2 norm, blind or not). Wavelets and Wavelet packets for confocal microscopy image restoration and deconvolution will be presented. Finally an invited talk of a well know researcher in the field will be given (the speaker will change every year, coming from INRA, Pasteur Institute, Curie Institute, Weizmann Institute, EPFL or ETHZ).

Prerequisites :

  • Basic course in image processing and in optimization

Content (slides):

  • Confocal microscopy: PSF, noise and Signal processing tools for image restoration (deconvolution, denoising): Fourier transform, sampling, convolution, filtering, introduction to inverse problems.
  • Markov Random Field for image restoration.
  • Variational approach for image restoration.
  • Regularized restoration of confocal microscopy images (Richardson Lucy algorithm, L2 and L1 regularization, PSF estimation).
  • Wavelet transform, complex wavelet Packets, application to restoration of confocal images.
  • Parameter estimation with complete or incomplete data.
  • Visit of INRA Sophia Antipolis microscopy plateform with Josiane Zerubia and Gilbert Engler (INRA) and discussions.

References :

  • Handbook of Biological Confocal Microscopy. James Pawley. Springer-Verlag, Revised edition, 2006.
  • Mathematical Problems in Image Processing, Aubert, Kornprobst, Springer Verlag, Applied Math- ematical Sciences , Vol. 147, 2006.
  • Markov Random Field Modeling in Image Analysis, Stan Z. Li, Springer Verlag, Revised edition, 2009.
  • A Wavelet Tour of Signal Processing: The Sparse Way, Stephane Mallat, Academic Press, Revised edition 2008.
  • On blind deconvoltion for thin layered confocal imaging. P. Pankajakshan and B. Zhang and L. Blanc-Féraud and Z. Kam and J.C. Olivo-Marin and J. Zerubia. Applied Optics, 48(21), July 2009.
  • Richardson-Lucy Algorithm with Total Variation Regularization for 3D Confocal Microscope Deconvolution. N. Dey and L. Blanc-Féraud and C. Zimmer and Z. Kam and P. Roux and J.C. Olivo-Marin and J. Zerubia. Microscopy Research Technique, 69: pages 260-266, 2006.
  • Guyon X., ``Champs aléatoires sur un réseau : modélisations, statistiques et applications'', Masson, 1993.