ITK Release 4/A2D2 Projects/Deconvolution Algorithms

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Motivation

Deconvolution is an image processing algorithm used to reduce blurring artifacts from images. It is often applied to fluorescence microscopy images, astronomical images, and images exhibiting motion blur.

Currently, reference deconvolution algorithms are not available in the default ITK source code distribution (though a number are available in this Insight Journal article).

Goals

  • Add analytical point-spread functions (PSFs) as image sources and fit them to experimental images of PSFs.
  • Add reference deconvolution algorithms including
    • Wiener filter
    • projected Landweber algorithm
    • Richardson-Lucy algorithm
    • a semi-blind algorithm that uses the analytical PSF model defined above to constrain the solution
  • Publish example blurred images with their corresponding PSF images
  • Incorporate these deconvolution algorithms into several popular image analysis programs geared toward biomedical researchers

Data

Team

  • Marc Niethammer (UNC Chapel Hill)
  • Russell Taylor (UNC Chapel Hill)
  • Cory Quammen (UNC Chapel Hill)
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