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Image Degradation in Microscopic Images: Avoidance, Artifacts, and Solutions

  • Joris RoelsEmail author
  • Jan Aelterman
  • Jonas De Vylder
  • Saskia Lippens
  • Hiêp Q. Luong
  • Christopher J. Guérin
  • Wilfried Philips
Chapter
Part of the Advances in Anatomy, Embryology and Cell Biology book series (ADVSANAT, volume 219)

Abstract

The goal of modern microscopy is to acquire high-quality image based data sets. A typical microscopy workflow is set up in order to address a specific biological question and involves different steps. The first step is to precisely define the biological question, in order to properly come to an experimental design for sample preparation and image acquisition. A better object representation allows biological users to draw more reliable scientific conclusions. Image restoration can manipulate the acquired data in an effort to reduce the impact of artifacts (spurious results) due to physical and technical limitations, resulting in a better representation of the object of interest. However, precise usage of these algorithms is necessary so as to avoid further artifacts that might influence the data analysis and bias the conclusions. It is essential to understand image acquisition, and how it introduces artifacts and degradations in the acquired data, so that their effects on subsequent analysis can be minimized. This paper provides an overview of the fundamental artifacts and degradations that affect many micrographs. We describe why artifacts appear, in what sense they impact overall image quality, and how to mitigate them by first improving the acquisition parameters and then applying proper image restoration techniques.

Keywords

Compression Ratio Point Spread Function JPEG Compression Lossy Compression Lossless Compression 
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.

Notes

Acknowledgements

This research has been made possible by the Agency for Innovation by Science and Technology in Flanders (IWT) and the iMinds BAHAMAS project (http://www.iminds.be/en/projects/2015/03/11/bahamas). We would like to thank Evelien Van Hamme (VIB—Bio Imaging Core/IRC/DMBR) for the microscopy images.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Joris Roels
    • 1
    • 2
    Email author
  • Jan Aelterman
    • 1
  • Jonas De Vylder
    • 1
  • Saskia Lippens
    • 2
    • 3
    • 4
  • Hiêp Q. Luong
    • 1
  • Christopher J. Guérin
    • 2
    • 3
    • 4
  • Wilfried Philips
    • 1
  1. 1.Department of Telecommunications and Information Processing - Image Processing and Interpretation/iMindsGhent UniversityGentBelgium
  2. 2.Inflammation Research Center, Flanders Institute for BiotechnologyZwijnaardeBelgium
  3. 3.Bio Imaging Core, Flanders Institute for BiotechnologyZwijnaardeBelgium
  4. 4.Department of Biomedical Molecular BiologyGhent UniversityZwijnaardeBelgium

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